Job Description Job Description: About Zipline Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations. Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe. We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.About You and The Role Zipline is seeking a Senior RF Desense Engineer to lead the architecture, analysis, mitigation, validation, and long-term improvement of RF desense performance across our autonomous aircraft and ground infrastructure. You will own receiver desense engineering from early system architecture through hardware integration, validation, manufacturing, certification, and field deployment. You will work across wireless platforms supporting 4G LTE, 5G NR, GNSS, Wi-Fi, ADS-B, UAT, Bluetooth, ISM radios, emerging Vehicle-to-Vehicle (V2V) communications, and future air-to-ground communication systems, ensuring receivers maintain robust performance despite increasingly dense RF and electronic environments. This role also owns the end-to-end electromagnetic shielding architecture across Zipline's wireless platforms. You will define shielding strategies spanning RF integrated circuits, front-end modules, connectors, cable harnesses, line-replaceable units (LRUs), subsystem enclosures, and complete products to control both internally generated and externally coupled interference. Working closely with electrical, mechanical, antenna, manufacturing, reliability, and systems teams, you will develop scalable shielding solutions that enable simultaneous operation of multiple high-power transmitters and high-sensitivity receivers-including precision GNSS systems-while meeting aggressive performance, reliability, manufacturability, weight, cost, and product lifetime requirements. While the primary focus of this role is receiver desense, you will also support broader RF coexistence efforts by contributing to system-level interference analysis, radio scheduling strategies, and multi-radio integration. You will collaborate closely with antenna, RF front-end, electrical, embedded software, systems, mechanical, flight test, manufacturing, reliability, certification, and cloud engineering teams to ensure Zipline's wireless systems perform reliably under real-world operating conditions.What You'll DoOwn RF desense architecture, analysis, mitigation, validation, and production support across Zipline aircraft, docks, droids, Zipping Points, and future autonomous logistics platforms.Develop receiver desense budgets and performance requirements for next-generation wireless platforms.Identify and mitigate receiver sensitivity degradation caused by onboard transmitters, switching power supplies, processors, high-speed digital interfaces, displays, motors, power electronics, and other electronic subsystems.Analyze conducted and radiated interference mechanisms including broadband noise coupling, harmonics, spurious emissions, blocking, intermodulation, passive intermodulation, and electromagnetic compatibility.Characterize RF coupling paths through PCBs, cables, antennas, enclosures, mechanical structures, power systems, and wiring harnesses.Develop practical mitigation strategies including shielding, filtering, grounding, PCB layout optimization, clock management, power supply noise reduction, frequency planning, and antenna isolation improvements.Define RF design guidelines that minimize desense risks early in product development.Define Zipline's end-to-end electromagnetic shielding architecture spanning RF ICs, front-end modules, PCB assemblies, connectors, cable harnesses, LRUs, subsystem enclosures, and complete products.Develop shielding strategies that minimize self-generated and externally coupled RF interference while balancing size, weight, thermal performance, manufacturability, serviceability, reliability, and cost.Specify shielding requirements for RF circuits, mixed-signal electronics, switching power supplies, processors, high-speed digital interfaces, motors, and power electronics to prevent receiver degradation.Design connector and cable interconnect shielding architectures including shield termination, grounding topology, common-mode current control, cable routing, connector selection, and bonding methods to minimize conducted and radiated emissions.Develop subsystem-level shielding strategies defining enclosure construction, gasket selection, aperture control, seam treatment, venting approaches, conductive coatings, and grounding interfaces to achieve predictable electromagnetic isolation.Lead product-level shielding architecture to ensure emissions from all subsystems remain below receiver susceptibility thresholds while supporting simultaneous operation of multiple transmitters and sensitive receivers.Develop shielding methodologies that enable reliable integration of LTE, 5G, GNSS, Wi-Fi, Bluetooth, ADS-B, UAT, ISM radios, telemetry, command-and-control, V2V communications, and future wireless technologies operating concurrently.Drive shielding design decisions through simulation, laboratory characterization, near-field scanning, EMI/EMC testing, environmental testing, flight testing, and structured root-cause analysis.Establish shielding design standards, verification methodologies, acceptance criteria, production inspection processes, and long-term design guidelines across Zipline's hardware platforms.Partner with mechanical engineering to design lightweight, manufacturable shielding solutions that maintain performance over the full environmental and operational life of the product.Define shielding strategies that protect high-precision GNSS receivers from onboard interference sources, enabling robust positioning performance under simultaneous multi-radio operation and dynamic flight conditions.Perform RF system analysis including receiver sensitivity, cascaded noise figure, blocking performance, dynamic range, interference budgeting, and system margin analysis.Collaborate closely with RF front-end and antenna engineers to optimize signal chains, antenna placement, installed performance, and isolation.Support PCB layout reviews, grounding strategies, shielding implementation, stack-up definition, and design-for-manufacturing activities.Develop laboratory validation methods using spectrum analyzers, vector network analyzers, vector signal analyzers, signal generators, near-field probes, OTA chambers, EMI receivers, and conducted RF measurements.Plan and execute RF desense characterization, conducted and over-the-air testing, environmental qualification, production verification, and flight testing.Investigate RF performance issues using laboratory measurements, simulation, production data, and structured root-cause analysis.Support RF coexistence activities including multi-radio interference analysis, wireless integration, radio scheduling strategies, and system-level performance optimization.Support regulatory and carrier certification activities including FCC, CE, ISED, PTCRB, GCF, carrier acceptance, aviation certifications, and international wireless and EMC certifications.Work closely with suppliers and manufacturing partners to establish RF acceptance criteria, production test methods, calibration procedures, shielding validation processes, and quality controls.Mentor engineers and help establish RF desense methodologies, shielding architectures, debugging processes, validation standards, and long-term RF performance roadmaps.What You'll BringBachelor's degree in Electrical Engineering or a related technical field.Typically 7 or more years of professional experience developing RF hardware or wireless communication systems for production products.Strong understanding of RF receiver architecture, cascaded receiver performance, sensitivity, noise figure, blocking, dynamic range, selectivity, and receiver optimization.Demonstrated experience investigating and resolving RF desense issues within complex wireless systems.Demonstrated experience developing shielding architectures from RF circuit level through complete products, including PCB shielding, connector shielding, cable shielding, enclosure design, subsystem isolation, LRU-level shielding, and product-level electromagnetic containment.Strong understanding of electromagnetic coupling mechanisms including conducted emissions, radiated emissions, harmonics, intermodulation, passive intermodulation, broadband digital noise, common-mode currents, grounding topology, shielding effectiveness, enclosure resonance, and practical mitigation techniques . click apply for full job details
08/05/2026
Full time
Job Description Job Description: About Zipline Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations. Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe. We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.About You and The Role Zipline is seeking a Senior RF Desense Engineer to lead the architecture, analysis, mitigation, validation, and long-term improvement of RF desense performance across our autonomous aircraft and ground infrastructure. You will own receiver desense engineering from early system architecture through hardware integration, validation, manufacturing, certification, and field deployment. You will work across wireless platforms supporting 4G LTE, 5G NR, GNSS, Wi-Fi, ADS-B, UAT, Bluetooth, ISM radios, emerging Vehicle-to-Vehicle (V2V) communications, and future air-to-ground communication systems, ensuring receivers maintain robust performance despite increasingly dense RF and electronic environments. This role also owns the end-to-end electromagnetic shielding architecture across Zipline's wireless platforms. You will define shielding strategies spanning RF integrated circuits, front-end modules, connectors, cable harnesses, line-replaceable units (LRUs), subsystem enclosures, and complete products to control both internally generated and externally coupled interference. Working closely with electrical, mechanical, antenna, manufacturing, reliability, and systems teams, you will develop scalable shielding solutions that enable simultaneous operation of multiple high-power transmitters and high-sensitivity receivers-including precision GNSS systems-while meeting aggressive performance, reliability, manufacturability, weight, cost, and product lifetime requirements. While the primary focus of this role is receiver desense, you will also support broader RF coexistence efforts by contributing to system-level interference analysis, radio scheduling strategies, and multi-radio integration. You will collaborate closely with antenna, RF front-end, electrical, embedded software, systems, mechanical, flight test, manufacturing, reliability, certification, and cloud engineering teams to ensure Zipline's wireless systems perform reliably under real-world operating conditions.What You'll DoOwn RF desense architecture, analysis, mitigation, validation, and production support across Zipline aircraft, docks, droids, Zipping Points, and future autonomous logistics platforms.Develop receiver desense budgets and performance requirements for next-generation wireless platforms.Identify and mitigate receiver sensitivity degradation caused by onboard transmitters, switching power supplies, processors, high-speed digital interfaces, displays, motors, power electronics, and other electronic subsystems.Analyze conducted and radiated interference mechanisms including broadband noise coupling, harmonics, spurious emissions, blocking, intermodulation, passive intermodulation, and electromagnetic compatibility.Characterize RF coupling paths through PCBs, cables, antennas, enclosures, mechanical structures, power systems, and wiring harnesses.Develop practical mitigation strategies including shielding, filtering, grounding, PCB layout optimization, clock management, power supply noise reduction, frequency planning, and antenna isolation improvements.Define RF design guidelines that minimize desense risks early in product development.Define Zipline's end-to-end electromagnetic shielding architecture spanning RF ICs, front-end modules, PCB assemblies, connectors, cable harnesses, LRUs, subsystem enclosures, and complete products.Develop shielding strategies that minimize self-generated and externally coupled RF interference while balancing size, weight, thermal performance, manufacturability, serviceability, reliability, and cost.Specify shielding requirements for RF circuits, mixed-signal electronics, switching power supplies, processors, high-speed digital interfaces, motors, and power electronics to prevent receiver degradation.Design connector and cable interconnect shielding architectures including shield termination, grounding topology, common-mode current control, cable routing, connector selection, and bonding methods to minimize conducted and radiated emissions.Develop subsystem-level shielding strategies defining enclosure construction, gasket selection, aperture control, seam treatment, venting approaches, conductive coatings, and grounding interfaces to achieve predictable electromagnetic isolation.Lead product-level shielding architecture to ensure emissions from all subsystems remain below receiver susceptibility thresholds while supporting simultaneous operation of multiple transmitters and sensitive receivers.Develop shielding methodologies that enable reliable integration of LTE, 5G, GNSS, Wi-Fi, Bluetooth, ADS-B, UAT, ISM radios, telemetry, command-and-control, V2V communications, and future wireless technologies operating concurrently.Drive shielding design decisions through simulation, laboratory characterization, near-field scanning, EMI/EMC testing, environmental testing, flight testing, and structured root-cause analysis.Establish shielding design standards, verification methodologies, acceptance criteria, production inspection processes, and long-term design guidelines across Zipline's hardware platforms.Partner with mechanical engineering to design lightweight, manufacturable shielding solutions that maintain performance over the full environmental and operational life of the product.Define shielding strategies that protect high-precision GNSS receivers from onboard interference sources, enabling robust positioning performance under simultaneous multi-radio operation and dynamic flight conditions.Perform RF system analysis including receiver sensitivity, cascaded noise figure, blocking performance, dynamic range, interference budgeting, and system margin analysis.Collaborate closely with RF front-end and antenna engineers to optimize signal chains, antenna placement, installed performance, and isolation.Support PCB layout reviews, grounding strategies, shielding implementation, stack-up definition, and design-for-manufacturing activities.Develop laboratory validation methods using spectrum analyzers, vector network analyzers, vector signal analyzers, signal generators, near-field probes, OTA chambers, EMI receivers, and conducted RF measurements.Plan and execute RF desense characterization, conducted and over-the-air testing, environmental qualification, production verification, and flight testing.Investigate RF performance issues using laboratory measurements, simulation, production data, and structured root-cause analysis.Support RF coexistence activities including multi-radio interference analysis, wireless integration, radio scheduling strategies, and system-level performance optimization.Support regulatory and carrier certification activities including FCC, CE, ISED, PTCRB, GCF, carrier acceptance, aviation certifications, and international wireless and EMC certifications.Work closely with suppliers and manufacturing partners to establish RF acceptance criteria, production test methods, calibration procedures, shielding validation processes, and quality controls.Mentor engineers and help establish RF desense methodologies, shielding architectures, debugging processes, validation standards, and long-term RF performance roadmaps.What You'll BringBachelor's degree in Electrical Engineering or a related technical field.Typically 7 or more years of professional experience developing RF hardware or wireless communication systems for production products.Strong understanding of RF receiver architecture, cascaded receiver performance, sensitivity, noise figure, blocking, dynamic range, selectivity, and receiver optimization.Demonstrated experience investigating and resolving RF desense issues within complex wireless systems.Demonstrated experience developing shielding architectures from RF circuit level through complete products, including PCB shielding, connector shielding, cable shielding, enclosure design, subsystem isolation, LRU-level shielding, and product-level electromagnetic containment.Strong understanding of electromagnetic coupling mechanisms including conducted emissions, radiated emissions, harmonics, intermodulation, passive intermodulation, broadband digital noise, common-mode currents, grounding topology, shielding effectiveness, enclosure resonance, and practical mitigation techniques . click apply for full job details
Job Description Job Description Samsung SDS America AI Team is researching the next generation of intelligent robotic systems that operate in the real world. Working with multiple robot hardware partners, we use their platforms to develop complete embodied AI systems, spanning data collection through teleoperation, policy training, and deployment on physical robots in real-world environments. We are looking for a Senior Physical AI Engineer to join the team developing this end-to-end pipeline. You will work hands-on with humanoid robots, collecting demonstration data through teleoperation, training learning-based policies, deploying them on the physical platform, and iterating through live test runs in real environments, not just simulation. You will also research dexterous manipulation, advancing the hand and grasping capabilities that enable robots to handle complex tasks. This role sits at the intersection of robotics, embodied AI, machine learning, and production software engineering. You will connect high-level AI models to physical robot behavior, enabling robots to perceive, learn, adapt, and act safely in dynamic environments. What sets our lab apart is the shared ownership and the path to impact. You will work alongside a small team that takes real ownership of what we develop here, helping shape research directions, building systems directly, and seeing your work move quickly from ideas to robot experiments on real hardware. Samsung SDS builds and operates systems that support manufacturing at scale across thousands of factory lines worldwide. The Physical AI capabilities we research here are aimed at that production environment, with a path that extends from a single robot today toward coordinated multi-robot systems on the factory floor. This is a hands-on research and engineering role spanning teleoperation, policy training, real-world deployment, low-latency control systems, simulation, and scalable AI training pipelines. If you enjoy working with robots that move, learn, and interact with the physical world, this role is for you. Responsibilities Design and develop intelligent robotic systems powered by modern AI and machine learning techniques Build scalable training pipelines for embodied AI and robot learning applications Develop production-grade robotics software in Python and related frameworks Train and deploy learning-based robotic policies using reinforcement learning and imitation learning approaches Integrate AI models with physical robot actuators, camera systems, and sensor pipelines Implement robotics control algorithms, kinematics, dynamics, and sensor fusion systems Work with simulation and synthetic data generation environments including Isaac Sim, MuJoCo, Sapien, or similar platforms Optimize low-latency inference and control systems for real-world robotic deployment Collaborate across robotics, AI, systems, and hardware teams to bring intelligent robotic platforms into production Contribute to the architecture of next-generation embodied AI systems Requirements 5+ years of industry experience in robotics, embodied AI, physical AI, or autonomous systems Bachelor's degree in Computer Science, Artificial Intelligence or relevant field Strong Python programming skills with experience building scalable production systems Hands-on experience building, training, and deploying machine learning systems for robotics applications Deep familiarity with reinforcement learning, imitation learning, and modern ML frameworks such as PyTorch Strong understanding of robotics fundamentals, including: - robot control systems - kinematics and dynamics - perception and sensor fusion - camera and tactile sensor integration Experience with robotics middleware such as ROS or ROS2 Experience working with simulation environments such as NVIDIA Isaac Sim, MuJoCo, Sapien, or equivalent platforms Strong debugging and systems engineering skills across software and hardware boundaries Experience deploying robotics systems into real-world physical environments Preferred Qualifications Experience with humanoid robotics or manipulation systems Background in autonomous systems or embodied foundation models Experience with GPU acceleration and distributed training systems Familiarity with synthetic data generation and sim-to-real transfer techniques Experience optimizing robotics systems for edge or embedded deployment Benefits Why Join US Get hands-on with a real humanoid robot. Train it, test it, and iterate on real hardware, not just in simulation. Research dexterous manipulation, pushing the frontier of robotic hands and grasping for complex real-world tasks. Build Physical AI that deploys at scale, into real manufacturing environments running across many thousands of factory lines worldwide. Work on frontier Physical AI and robotics technologies that bridge advanced AI with real-world robotic behavior. Collaborate with a highly technical, fast-moving research/engineering team. Help shape a new robotics effort from its earliest stage. Samsung SDSA offers a competitive salary, and a comprehensive suite of programs to support our employees: Top-notch medical, dental, vision and prescription fully covered for You and Your family Wellness program Parental leave 401K match and savings plan Flexible spending accounts Life insurance Paid Holidays Paid Time off Additional perks The base salary range for this Mountain View, CA role is $200,000 to $270,000. Individual pay is determined by multiple factors, including job-related skills, experience, relevant training, and specific geographic location. Your recruiter can share more about the total compensation package-which may include performance bonuses, and comprehensive benefits-during the hiring process. Samsung SDS America, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, status as a protected veteran, marital status, genetic information, medical condition, or any other characteristic protected by law. We are committed to providing reasonable accommodations to participate in the job application or interview process for candidates with disabilities. If you need assistance and/or a reasonable accommodation, please send your request the recruiter.
08/05/2026
Full time
Job Description Job Description Samsung SDS America AI Team is researching the next generation of intelligent robotic systems that operate in the real world. Working with multiple robot hardware partners, we use their platforms to develop complete embodied AI systems, spanning data collection through teleoperation, policy training, and deployment on physical robots in real-world environments. We are looking for a Senior Physical AI Engineer to join the team developing this end-to-end pipeline. You will work hands-on with humanoid robots, collecting demonstration data through teleoperation, training learning-based policies, deploying them on the physical platform, and iterating through live test runs in real environments, not just simulation. You will also research dexterous manipulation, advancing the hand and grasping capabilities that enable robots to handle complex tasks. This role sits at the intersection of robotics, embodied AI, machine learning, and production software engineering. You will connect high-level AI models to physical robot behavior, enabling robots to perceive, learn, adapt, and act safely in dynamic environments. What sets our lab apart is the shared ownership and the path to impact. You will work alongside a small team that takes real ownership of what we develop here, helping shape research directions, building systems directly, and seeing your work move quickly from ideas to robot experiments on real hardware. Samsung SDS builds and operates systems that support manufacturing at scale across thousands of factory lines worldwide. The Physical AI capabilities we research here are aimed at that production environment, with a path that extends from a single robot today toward coordinated multi-robot systems on the factory floor. This is a hands-on research and engineering role spanning teleoperation, policy training, real-world deployment, low-latency control systems, simulation, and scalable AI training pipelines. If you enjoy working with robots that move, learn, and interact with the physical world, this role is for you. Responsibilities Design and develop intelligent robotic systems powered by modern AI and machine learning techniques Build scalable training pipelines for embodied AI and robot learning applications Develop production-grade robotics software in Python and related frameworks Train and deploy learning-based robotic policies using reinforcement learning and imitation learning approaches Integrate AI models with physical robot actuators, camera systems, and sensor pipelines Implement robotics control algorithms, kinematics, dynamics, and sensor fusion systems Work with simulation and synthetic data generation environments including Isaac Sim, MuJoCo, Sapien, or similar platforms Optimize low-latency inference and control systems for real-world robotic deployment Collaborate across robotics, AI, systems, and hardware teams to bring intelligent robotic platforms into production Contribute to the architecture of next-generation embodied AI systems Requirements 5+ years of industry experience in robotics, embodied AI, physical AI, or autonomous systems Bachelor's degree in Computer Science, Artificial Intelligence or relevant field Strong Python programming skills with experience building scalable production systems Hands-on experience building, training, and deploying machine learning systems for robotics applications Deep familiarity with reinforcement learning, imitation learning, and modern ML frameworks such as PyTorch Strong understanding of robotics fundamentals, including: - robot control systems - kinematics and dynamics - perception and sensor fusion - camera and tactile sensor integration Experience with robotics middleware such as ROS or ROS2 Experience working with simulation environments such as NVIDIA Isaac Sim, MuJoCo, Sapien, or equivalent platforms Strong debugging and systems engineering skills across software and hardware boundaries Experience deploying robotics systems into real-world physical environments Preferred Qualifications Experience with humanoid robotics or manipulation systems Background in autonomous systems or embodied foundation models Experience with GPU acceleration and distributed training systems Familiarity with synthetic data generation and sim-to-real transfer techniques Experience optimizing robotics systems for edge or embedded deployment Benefits Why Join US Get hands-on with a real humanoid robot. Train it, test it, and iterate on real hardware, not just in simulation. Research dexterous manipulation, pushing the frontier of robotic hands and grasping for complex real-world tasks. Build Physical AI that deploys at scale, into real manufacturing environments running across many thousands of factory lines worldwide. Work on frontier Physical AI and robotics technologies that bridge advanced AI with real-world robotic behavior. Collaborate with a highly technical, fast-moving research/engineering team. Help shape a new robotics effort from its earliest stage. Samsung SDSA offers a competitive salary, and a comprehensive suite of programs to support our employees: Top-notch medical, dental, vision and prescription fully covered for You and Your family Wellness program Parental leave 401K match and savings plan Flexible spending accounts Life insurance Paid Holidays Paid Time off Additional perks The base salary range for this Mountain View, CA role is $200,000 to $270,000. Individual pay is determined by multiple factors, including job-related skills, experience, relevant training, and specific geographic location. Your recruiter can share more about the total compensation package-which may include performance bonuses, and comprehensive benefits-during the hiring process. Samsung SDS America, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, status as a protected veteran, marital status, genetic information, medical condition, or any other characteristic protected by law. We are committed to providing reasonable accommodations to participate in the job application or interview process for candidates with disabilities. If you need assistance and/or a reasonable accommodation, please send your request the recruiter.
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
08/05/2026
Full time
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
08/05/2026
Full time
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
Job Description Job Description Senior Autonomy Engineer About the Company This aerospace startup is reshaping how the world connects from above. The team is developing solar-powered, long-endurance UAVs that operate at the edge of the atmosphere, delivering next-generation, low-latency communication capabilities to areas traditional satellite and ground-based networks cannot serve well. The vision is to redefine global connectivity for everything from underserved regions and disaster response to dynamic, mission-critical coverage. Backed by top-tier investors and led by a tight team of operators and engineers from the most respected names in aerospace, defense, and telecom, this is a rare ground-floor opportunity. They are lean, builder-led, and moving fast toward a near-term flight demonstration. This team has the technical depth, the network, and the timing to leap past incumbents and define the category. We prefer this person to be located in the Bay Area and onsite at headquarters, but for the right candidate we may consider a hybrid arrangement. About the Role This team is looking for a Senior Autonomy Engineer to own the design, architecture, and development of the entire autonomy software stack across the vehicle, payload, and ground infrastructure. As a true founding-team engineer, this person will be a world-class individual contributor and architect, with full latitude to shape how the aircraft flies, recovers, and eventually coordinates as a fleet. This is not a maintenance seat. It is the chance to define the autonomy platform from the ground up and watch your code fly. What You'll Own End-to-end autonomy architecture across vehicle, payload, and ground infrastructure for a long-endurance, high-altitude aircraft Mission management and behavioral executive: design the high-level state machines, behavior trees, and contingency logic that govern mission phases, abort behaviors, fault response, and payload coordination. Path and trajectory planning: build the algorithms for auto-takeoff, landing, dynamic waypoint navigation, geofencing, and end-to-end autonomous routing. Scale toward cooperative and non-cooperative avoidance and energy-aware planning that accounts for battery state of charge, expected solar harvest, and predicted spatial wind fields. Health, status, and fault detection: design robust fault detection and isolation that distinguishes healthy from faulty sensors and actuators, monitors system health, and triggers safe contingency behaviors on board in real time. Fleet management and simulation: build the centralized software that coordinates multiple vehicles across multiple sites, and stand up the cloud infrastructure for large-scale distributed simulation and log analysis. Infrastructure and testing: design and optimize CI/CD pipelines for autonomy software, drive SIL and HIL validation, and own flight readiness for early prototypes. What We're Looking For Deep, hands-on experience with path planning algorithms, finite state machines, and behavior trees. You have shipped autonomy that has flown or driven in the real world, not just in simulation. Strong production-level software engineering skill in a typed language. Heavy preference for Rust. C++ also strongly considered for the right profile. Broad systems architecture instincts. You are comfortable architecting complex, scalable software that bridges embedded vehicle software, ground systems, and cloud-based fleet managers. Embedded software experience on complex hardware platforms. Flying vehicles preferred, but robotics, autonomous ground systems, and other high-stakes hardware count. Ability to move fast and build in ambiguity. You reach for first principles rather than industry standards when the standards do not yet exist for the problem. Strong physics or GNC-adjacent intuition is a plus. The ability to look at flight logs and reason not only about whether mission management responded correctly, but why the aircraft is behaving the way it is, makes you stand out. A strong problem-solving mindset with a bias for action and excellent collaboration instincts. Excitement to be part of an ambitious, technically rigorous founding team, and a desire to do the best work of your career here. Benefits Why You'll Love Working Here Join a powerhouse team of brilliant builders Collaborate with a tight-knit crew of deeply technical operators and engineers from the most respected programs in aerospace, defense, and telecom. You will work alongside founders and leaders with a track record of shipping at the highest bar. Competitive startup salary Be paid well to do the most energizing work of your career. Ground-floor equity Own meaningful upside from day one. Shape the trajectory of the company and participate fully in the value you help create. Excellent health insurance Strong medical coverage so you can stay healthy while pushing the boundaries of what is possible. Dog-friendly office with Bay views Bring your pup and enjoy a beautiful workspace with panoramic water views that spark creativity and focus. Work on a uniquely hard problem Architect autonomy for an aircraft that lives at the edge of the atmosphere, where the wind is often faster than the vehicle and every kilogram, watt, and line of code matters. This is the kind of problem that nerd-snipes the best autonomy engineers in the world. About AdAstra AdAstra Talent Advisors is a headhunting and talent advising firm focused on the Climate, Space, and Defense sectors of Hard Tech. We specialize in pairing highly technical and executive talent with some of the world's leading Hard Tech startups. At AdAstra, we catalyze the innovations that future generations depend on by placing the right people in the right seats. Our dedicated work enables inconceivable technology from Earth, to the stars. And it's all because of trailblazing talent like you - those driven to do what's never been done before. We care about long term relationships with both candidates and companies. Even if the role we initially discuss isn't a perfect fit, it's likely we'll have something relevant to share with you in the future. Join us on our journey by following along via LinkedIn! CEO, Seyka Mejeur LinkedIn profile CTO / COO, Brian Mejeur LinkedIn profile AdAstra Talent Advisors LinkedIn profile AdAstra Website
08/05/2026
Full time
Job Description Job Description Senior Autonomy Engineer About the Company This aerospace startup is reshaping how the world connects from above. The team is developing solar-powered, long-endurance UAVs that operate at the edge of the atmosphere, delivering next-generation, low-latency communication capabilities to areas traditional satellite and ground-based networks cannot serve well. The vision is to redefine global connectivity for everything from underserved regions and disaster response to dynamic, mission-critical coverage. Backed by top-tier investors and led by a tight team of operators and engineers from the most respected names in aerospace, defense, and telecom, this is a rare ground-floor opportunity. They are lean, builder-led, and moving fast toward a near-term flight demonstration. This team has the technical depth, the network, and the timing to leap past incumbents and define the category. We prefer this person to be located in the Bay Area and onsite at headquarters, but for the right candidate we may consider a hybrid arrangement. About the Role This team is looking for a Senior Autonomy Engineer to own the design, architecture, and development of the entire autonomy software stack across the vehicle, payload, and ground infrastructure. As a true founding-team engineer, this person will be a world-class individual contributor and architect, with full latitude to shape how the aircraft flies, recovers, and eventually coordinates as a fleet. This is not a maintenance seat. It is the chance to define the autonomy platform from the ground up and watch your code fly. What You'll Own End-to-end autonomy architecture across vehicle, payload, and ground infrastructure for a long-endurance, high-altitude aircraft Mission management and behavioral executive: design the high-level state machines, behavior trees, and contingency logic that govern mission phases, abort behaviors, fault response, and payload coordination. Path and trajectory planning: build the algorithms for auto-takeoff, landing, dynamic waypoint navigation, geofencing, and end-to-end autonomous routing. Scale toward cooperative and non-cooperative avoidance and energy-aware planning that accounts for battery state of charge, expected solar harvest, and predicted spatial wind fields. Health, status, and fault detection: design robust fault detection and isolation that distinguishes healthy from faulty sensors and actuators, monitors system health, and triggers safe contingency behaviors on board in real time. Fleet management and simulation: build the centralized software that coordinates multiple vehicles across multiple sites, and stand up the cloud infrastructure for large-scale distributed simulation and log analysis. Infrastructure and testing: design and optimize CI/CD pipelines for autonomy software, drive SIL and HIL validation, and own flight readiness for early prototypes. What We're Looking For Deep, hands-on experience with path planning algorithms, finite state machines, and behavior trees. You have shipped autonomy that has flown or driven in the real world, not just in simulation. Strong production-level software engineering skill in a typed language. Heavy preference for Rust. C++ also strongly considered for the right profile. Broad systems architecture instincts. You are comfortable architecting complex, scalable software that bridges embedded vehicle software, ground systems, and cloud-based fleet managers. Embedded software experience on complex hardware platforms. Flying vehicles preferred, but robotics, autonomous ground systems, and other high-stakes hardware count. Ability to move fast and build in ambiguity. You reach for first principles rather than industry standards when the standards do not yet exist for the problem. Strong physics or GNC-adjacent intuition is a plus. The ability to look at flight logs and reason not only about whether mission management responded correctly, but why the aircraft is behaving the way it is, makes you stand out. A strong problem-solving mindset with a bias for action and excellent collaboration instincts. Excitement to be part of an ambitious, technically rigorous founding team, and a desire to do the best work of your career here. Benefits Why You'll Love Working Here Join a powerhouse team of brilliant builders Collaborate with a tight-knit crew of deeply technical operators and engineers from the most respected programs in aerospace, defense, and telecom. You will work alongside founders and leaders with a track record of shipping at the highest bar. Competitive startup salary Be paid well to do the most energizing work of your career. Ground-floor equity Own meaningful upside from day one. Shape the trajectory of the company and participate fully in the value you help create. Excellent health insurance Strong medical coverage so you can stay healthy while pushing the boundaries of what is possible. Dog-friendly office with Bay views Bring your pup and enjoy a beautiful workspace with panoramic water views that spark creativity and focus. Work on a uniquely hard problem Architect autonomy for an aircraft that lives at the edge of the atmosphere, where the wind is often faster than the vehicle and every kilogram, watt, and line of code matters. This is the kind of problem that nerd-snipes the best autonomy engineers in the world. About AdAstra AdAstra Talent Advisors is a headhunting and talent advising firm focused on the Climate, Space, and Defense sectors of Hard Tech. We specialize in pairing highly technical and executive talent with some of the world's leading Hard Tech startups. At AdAstra, we catalyze the innovations that future generations depend on by placing the right people in the right seats. Our dedicated work enables inconceivable technology from Earth, to the stars. And it's all because of trailblazing talent like you - those driven to do what's never been done before. We care about long term relationships with both candidates and companies. Even if the role we initially discuss isn't a perfect fit, it's likely we'll have something relevant to share with you in the future. Join us on our journey by following along via LinkedIn! CEO, Seyka Mejeur LinkedIn profile CTO / COO, Brian Mejeur LinkedIn profile AdAstra Talent Advisors LinkedIn profile AdAstra Website
Job Description Job Description About the Role Teserac is building neuron , a unified AI-native platform for data center observability, intelligence, and workflow automation. neuron processes real-time telemetry from thousands of sensors, meters, and control systems across heterogeneous environments - giving infrastructure owners the visibility to monitor, analyze, automate, and proactively manage power operations with full situational awareness. An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited to build intelligent systems at the intersection of applied AI and critical infrastructure. You will work across the full AI development lifecycle - from data pipelines and model integration to agentic orchestration, evaluation, and production support - collaborating closely with a small, fast-moving engineering team. This is not a research-only role, but research thinking matters here. You will be expected to read papers, stay ahead of the field, and bring ideas to the table - then build them into production systems. Who We Are Looking For We care more about how you think than how many years are on your resume. This role is open to both junior and senior candidates. What matters is: You are genuinely excited about AI and infrastructure - not just one of them You learn fast, go deep, and can hold your own in a technical debate You have the engineering fundamentals to ship reliable systems You are proactive, curious, and comfortable with a steep learning curve You want to work on something technically hard that actually matters in the physical world If you are early in your career but have strong fundamentals, a track record of self-directed learning, and a portfolio that shows you build things - we want to hear from you. What You Will Work On Multi-agent orchestration and LLM-driven triage workflows Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry Retrieval-augmented knowledge systems for operations teams Data and ML pipelines - ingestion, ETL, and dataset construction Fine-tuning and post-training of language models for operational use cases AI observability, evaluation frameworks, and production performance benchmarking Responsibilities Design, develop, and maintain AI-powered applications and automation workflows Integrate and optimize LLM APIs for production use cases Build and refine retrieval and knowledge-augmentation pipelines Develop evaluation frameworks to benchmark AI system performance Implement monitoring, tracing, and debugging capabilities for AI systems Read and synthesize relevant research; bring ideas forward and debate them with the team Contribute to AI architecture decisions and production hardening Stay current with the rapidly evolving AI/ML landscape Requirements Required Degree in Computer Science, Machine Learning, Mathematics, or a related field - or equivalent demonstrated experience Strong proficiency in Python Solid software engineering fundamentals: testing, version control, CI/CD Experience working with LLM APIs in applied contexts Familiarity with agentic system concepts - tool/function-calling, agent frameworks Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.) Ability to read ML research papers and translate ideas into practical experiments Strong analytical thinking and clear communication - you can argue a position and update it when wrong Preferred Professional AI/ML engineering experience (any level) Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus Time-series modeling - forecasting and anomaly/failure prediction on multivariate data Experience fine-tuning or post-training language models PyTorch and/or model serving frameworks (e.g., vLLM) Experience building data and ML pipelines - ingestion, ETL, dataset construction Familiarity with cloud ML platforms, particularly GCP (Vertex AI) LLM evaluation and benchmarking: harness design and eval loop development Domain experience with data center or industrial telemetry, BMS/OT protocols (Niagara, BACnet/Modbus) Background in DevOps, distributed systems, or observability tooling Benefits Health Care Plan (Medical, Dental & Vision) Paid Time Off (Vacation, Sick & Public Holidays) Free Food & Snacks Stock Option Plan 401(k)
08/05/2026
Full time
Job Description Job Description About the Role Teserac is building neuron , a unified AI-native platform for data center observability, intelligence, and workflow automation. neuron processes real-time telemetry from thousands of sensors, meters, and control systems across heterogeneous environments - giving infrastructure owners the visibility to monitor, analyze, automate, and proactively manage power operations with full situational awareness. An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited to build intelligent systems at the intersection of applied AI and critical infrastructure. You will work across the full AI development lifecycle - from data pipelines and model integration to agentic orchestration, evaluation, and production support - collaborating closely with a small, fast-moving engineering team. This is not a research-only role, but research thinking matters here. You will be expected to read papers, stay ahead of the field, and bring ideas to the table - then build them into production systems. Who We Are Looking For We care more about how you think than how many years are on your resume. This role is open to both junior and senior candidates. What matters is: You are genuinely excited about AI and infrastructure - not just one of them You learn fast, go deep, and can hold your own in a technical debate You have the engineering fundamentals to ship reliable systems You are proactive, curious, and comfortable with a steep learning curve You want to work on something technically hard that actually matters in the physical world If you are early in your career but have strong fundamentals, a track record of self-directed learning, and a portfolio that shows you build things - we want to hear from you. What You Will Work On Multi-agent orchestration and LLM-driven triage workflows Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry Retrieval-augmented knowledge systems for operations teams Data and ML pipelines - ingestion, ETL, and dataset construction Fine-tuning and post-training of language models for operational use cases AI observability, evaluation frameworks, and production performance benchmarking Responsibilities Design, develop, and maintain AI-powered applications and automation workflows Integrate and optimize LLM APIs for production use cases Build and refine retrieval and knowledge-augmentation pipelines Develop evaluation frameworks to benchmark AI system performance Implement monitoring, tracing, and debugging capabilities for AI systems Read and synthesize relevant research; bring ideas forward and debate them with the team Contribute to AI architecture decisions and production hardening Stay current with the rapidly evolving AI/ML landscape Requirements Required Degree in Computer Science, Machine Learning, Mathematics, or a related field - or equivalent demonstrated experience Strong proficiency in Python Solid software engineering fundamentals: testing, version control, CI/CD Experience working with LLM APIs in applied contexts Familiarity with agentic system concepts - tool/function-calling, agent frameworks Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.) Ability to read ML research papers and translate ideas into practical experiments Strong analytical thinking and clear communication - you can argue a position and update it when wrong Preferred Professional AI/ML engineering experience (any level) Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus Time-series modeling - forecasting and anomaly/failure prediction on multivariate data Experience fine-tuning or post-training language models PyTorch and/or model serving frameworks (e.g., vLLM) Experience building data and ML pipelines - ingestion, ETL, dataset construction Familiarity with cloud ML platforms, particularly GCP (Vertex AI) LLM evaluation and benchmarking: harness design and eval loop development Domain experience with data center or industrial telemetry, BMS/OT protocols (Niagara, BACnet/Modbus) Background in DevOps, distributed systems, or observability tooling Benefits Health Care Plan (Medical, Dental & Vision) Paid Time Off (Vacation, Sick & Public Holidays) Free Food & Snacks Stock Option Plan 401(k)
Job Description Job Description About Gridware Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware's advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit . Responsibilities Develop algorithms that improve the speed, accuracy, and reliability of Gridware's automated hazard detection systems Work with multimodal time-series and spatial sensor data across diverse sampling rates and noise characteristics. Design models that are robust, interpretable, and deployable in production environments. Live in the data; help curate & share strategic & well-defined datasets that help solve our highest-value challenges Explore advanced approaches such as graph-based learning for grid topology reasoning, geospatial modeling and localization and multimodal fusion across acoustic, magnetic, vibration, electrical, and visual signals Production Engineering Write clean, scalable, well-tested Python code that integrates into a large shared codebase. Build end-to-end ML pipelines including data processing, feature extraction, training, evaluation, and deployment. Optimize models for performance, reliability, and real-world constraints. Collaborate on infrastructure for model monitoring, validation, and continuous improvement. Collaboration & Communication Translate complex analyses into clear insights for engineers, operators, and leadership. Frame solutions to ambiguous, open-ended problems to achieve buy-in from various stakeholders by focusing on the business impact of your projects Communicate uncertainty, tradeoffs, and model behavior effectively. Partner cross-functionally with software, data engineering, product, and event-reporting teams. Help shape technical direction and best practices for ML at Gridware. This includes exemplifying standards for experiment tracking, model versioning, reproducibility, and lifecycle management. Required Skills 5+ years of experience in machine learning, signal processing, or applied physics in production environments. Strong programming skills in Python and experience contributing to large, shared codebases. Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows Excellent written and verbal communication, especially explaining data and models clearly. Bonus Skills Experience with Graph Neural Networks or learning over physical/topological systems. Familiarity with power systems, embedded sensing, or edge ML. Proven experience with time-series modeling and noisy real-world sensor data. Experience with multimodal learning or sensor fusion. Track record of technical leadership or mentoring. This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply! Benefits Health, Dental & Vision (Gold and Platinum with some providers plans fully covered) Paid parental leave Alternating day off (every other Monday) "Off the Grid", a two week per year paid break for all employees. Commuter allowance Company-paid training
08/05/2026
Full time
Job Description Job Description About Gridware Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware's advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit . Responsibilities Develop algorithms that improve the speed, accuracy, and reliability of Gridware's automated hazard detection systems Work with multimodal time-series and spatial sensor data across diverse sampling rates and noise characteristics. Design models that are robust, interpretable, and deployable in production environments. Live in the data; help curate & share strategic & well-defined datasets that help solve our highest-value challenges Explore advanced approaches such as graph-based learning for grid topology reasoning, geospatial modeling and localization and multimodal fusion across acoustic, magnetic, vibration, electrical, and visual signals Production Engineering Write clean, scalable, well-tested Python code that integrates into a large shared codebase. Build end-to-end ML pipelines including data processing, feature extraction, training, evaluation, and deployment. Optimize models for performance, reliability, and real-world constraints. Collaborate on infrastructure for model monitoring, validation, and continuous improvement. Collaboration & Communication Translate complex analyses into clear insights for engineers, operators, and leadership. Frame solutions to ambiguous, open-ended problems to achieve buy-in from various stakeholders by focusing on the business impact of your projects Communicate uncertainty, tradeoffs, and model behavior effectively. Partner cross-functionally with software, data engineering, product, and event-reporting teams. Help shape technical direction and best practices for ML at Gridware. This includes exemplifying standards for experiment tracking, model versioning, reproducibility, and lifecycle management. Required Skills 5+ years of experience in machine learning, signal processing, or applied physics in production environments. Strong programming skills in Python and experience contributing to large, shared codebases. Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows Excellent written and verbal communication, especially explaining data and models clearly. Bonus Skills Experience with Graph Neural Networks or learning over physical/topological systems. Familiarity with power systems, embedded sensing, or edge ML. Proven experience with time-series modeling and noisy real-world sensor data. Experience with multimodal learning or sensor fusion. Track record of technical leadership or mentoring. This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply! Benefits Health, Dental & Vision (Gold and Platinum with some providers plans fully covered) Paid parental leave Alternating day off (every other Monday) "Off the Grid", a two week per year paid break for all employees. Commuter allowance Company-paid training
Job Description Job Description About Cyngn Based in Mountain View, CA, Cyngn is a publicly-traded autonomous technology company. We deploy self-driving industrial vehicles like forklifts and tuggers to factories, warehouses, and other facilities throughout North America. To build this emergent technology, we are looking for innovative, motivated, and experienced leaders to join us and move this field forward. If you like to build, tinker, and create with a team of trusted and passionate colleagues, then Cyngn is the place for you. Key reasons to join Cyngn: We are small and big. With under 100 employees, Cyngn operates with the energy of a startup. On the other hand, we're publicly traded. This means our employees not only work in close-knit teams with mentorship from company leaders-they also get access to the liquidity of our publicly-traded equity. We build today and deploy tomorrow. Our autonomous vehicles aren't just test concepts-they're deployed to real clients right now. That means your work will have a tangible, visible impact. We aren't robots. We just develop them. We're a welcoming, diverse team of sharp thinkers and kind humans. Collaboration and trust drive our creative environment. At Cyngn, everyone's perspective matters-and that's what powers our innovation. About this role: Cyngn builds autonomous industrial vehicle solutions that run in real warehouses and outdoor yards-not demos. As a Robotics Integration Engineer (Mid-Junior) , you'll help bring autonomy to life by integrating hardware + sensors + vehicle software into a reliable, production-ready stack. This is a hands-on role working with Linux systems , real sensors, and real vehicles-partnering closely with senior robotics, autonomy, and platform engineers to ship systems that are stable, debuggable, and performant in industrial environments. Responsibilities Integrate and validate sensors such as LiDAR, cameras, IMU/GNSS , and other vehicle hardware. Own mission-critical system pieces: state management , health monitoring, diagnostics, logging, and fleet-ready tooling. Work on vehicle communications including CAN bus (interfaces, message handling, reliability, basic ECU/firmware touchpoints). Build and maintain the glue that makes the stack work: drivers, bring-up scripts, config management, calibration workflows , and time synchronization basics. Troubleshoot complex issues across hardware + software + networking (timing drift, dropped frames, driver issues, flaky connections, bandwidth constraints). Profile and optimize performance for real-time-ish workloads (high-bandwidth sensor streams, CPU/memory bottlenecks, startup stability). Help create and maintain integration tests and validation workflows (reproducible tests, automated checks, regression catches, log replay). Collaborate across perception, localization, controls, and product teams to integrate systems cleanly and ship improvements quickly. Write clear documentation for integration procedures, system configuration, and "how to debug this when it breaks." Qualifications 2-4+ years in robotics integration, autonomy, embedded/systems engineering, or adjacent experience working close to hardware. Strong programming ability in: C++ (systems/performance -critical code) Python (tooling, automation, integration glue) Shell scripting (Linux workflows, debugging, automation) Solid experience with Linux (Ubuntu) , including building, packaging, and running systems in the field. Comfort with sensor + hardware bring-up (drivers, calibration workflows, time sync concepts, logs, reproducible setup). Understanding of networking fundamentals (TCP/UDP, bandwidth/latency tradeoffs, basic multicast, and debugging with common tools). Strong debugging instincts: you can form a hypothesis, gather evidence, and drive to root cause across layers. Clear communicator with good documentation habits and a low-ego, team-first approach. Bonus Qualifications Experience with ROS 2 (nodes, launch, TF2, bags, QoS) or other robotics middleware frameworks. Experience with CAN tooling (SocketCAN, DBC workflows) and/or ECU/firmware update flows. Experience with containerized deployments (e.g., Docker) or production deployment patterns on vehicles. Familiarity with profiling tools (perf, top/htop, valgrind, gdb) and performance tuning. Exposure to OTA / device management systems (e.g., AWS Greengrass) or fleet rollout practices. Understanding of safety-oriented development practices (fault handling, watchdogs, redundancy concepts). Experience with simulation environments (e.g., NVIDIA Isaac Sim , Gazebo, or similar) for integration and regression testing. CI/CD experience for robotics stacks (automated builds/tests, hardware-in-the-loop or log replay workflows). Benefits & Perks Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge) Life, Short-term and long-term disability insurance (Cyngn funds 100% of premiums) Company 401(k) Commuter Benefits Flexible vacation policy Remote or hybrid work opportunities Sabbatical leave opportunity after 5 years with the company Paid Parental Leave Daily lunches for in-office employees Monthly meal and tech allowances for remote employees Please note salary range is for Bay Area residents - we're still accepting remote applicants! We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
08/05/2026
Full time
Job Description Job Description About Cyngn Based in Mountain View, CA, Cyngn is a publicly-traded autonomous technology company. We deploy self-driving industrial vehicles like forklifts and tuggers to factories, warehouses, and other facilities throughout North America. To build this emergent technology, we are looking for innovative, motivated, and experienced leaders to join us and move this field forward. If you like to build, tinker, and create with a team of trusted and passionate colleagues, then Cyngn is the place for you. Key reasons to join Cyngn: We are small and big. With under 100 employees, Cyngn operates with the energy of a startup. On the other hand, we're publicly traded. This means our employees not only work in close-knit teams with mentorship from company leaders-they also get access to the liquidity of our publicly-traded equity. We build today and deploy tomorrow. Our autonomous vehicles aren't just test concepts-they're deployed to real clients right now. That means your work will have a tangible, visible impact. We aren't robots. We just develop them. We're a welcoming, diverse team of sharp thinkers and kind humans. Collaboration and trust drive our creative environment. At Cyngn, everyone's perspective matters-and that's what powers our innovation. About this role: Cyngn builds autonomous industrial vehicle solutions that run in real warehouses and outdoor yards-not demos. As a Robotics Integration Engineer (Mid-Junior) , you'll help bring autonomy to life by integrating hardware + sensors + vehicle software into a reliable, production-ready stack. This is a hands-on role working with Linux systems , real sensors, and real vehicles-partnering closely with senior robotics, autonomy, and platform engineers to ship systems that are stable, debuggable, and performant in industrial environments. Responsibilities Integrate and validate sensors such as LiDAR, cameras, IMU/GNSS , and other vehicle hardware. Own mission-critical system pieces: state management , health monitoring, diagnostics, logging, and fleet-ready tooling. Work on vehicle communications including CAN bus (interfaces, message handling, reliability, basic ECU/firmware touchpoints). Build and maintain the glue that makes the stack work: drivers, bring-up scripts, config management, calibration workflows , and time synchronization basics. Troubleshoot complex issues across hardware + software + networking (timing drift, dropped frames, driver issues, flaky connections, bandwidth constraints). Profile and optimize performance for real-time-ish workloads (high-bandwidth sensor streams, CPU/memory bottlenecks, startup stability). Help create and maintain integration tests and validation workflows (reproducible tests, automated checks, regression catches, log replay). Collaborate across perception, localization, controls, and product teams to integrate systems cleanly and ship improvements quickly. Write clear documentation for integration procedures, system configuration, and "how to debug this when it breaks." Qualifications 2-4+ years in robotics integration, autonomy, embedded/systems engineering, or adjacent experience working close to hardware. Strong programming ability in: C++ (systems/performance -critical code) Python (tooling, automation, integration glue) Shell scripting (Linux workflows, debugging, automation) Solid experience with Linux (Ubuntu) , including building, packaging, and running systems in the field. Comfort with sensor + hardware bring-up (drivers, calibration workflows, time sync concepts, logs, reproducible setup). Understanding of networking fundamentals (TCP/UDP, bandwidth/latency tradeoffs, basic multicast, and debugging with common tools). Strong debugging instincts: you can form a hypothesis, gather evidence, and drive to root cause across layers. Clear communicator with good documentation habits and a low-ego, team-first approach. Bonus Qualifications Experience with ROS 2 (nodes, launch, TF2, bags, QoS) or other robotics middleware frameworks. Experience with CAN tooling (SocketCAN, DBC workflows) and/or ECU/firmware update flows. Experience with containerized deployments (e.g., Docker) or production deployment patterns on vehicles. Familiarity with profiling tools (perf, top/htop, valgrind, gdb) and performance tuning. Exposure to OTA / device management systems (e.g., AWS Greengrass) or fleet rollout practices. Understanding of safety-oriented development practices (fault handling, watchdogs, redundancy concepts). Experience with simulation environments (e.g., NVIDIA Isaac Sim , Gazebo, or similar) for integration and regression testing. CI/CD experience for robotics stacks (automated builds/tests, hardware-in-the-loop or log replay workflows). Benefits & Perks Health benefits (Medical, Dental, Vision, HSA and FSA (Health & Dependent Daycare), Employee Assistance Program, 1:1 Health Concierge) Life, Short-term and long-term disability insurance (Cyngn funds 100% of premiums) Company 401(k) Commuter Benefits Flexible vacation policy Remote or hybrid work opportunities Sabbatical leave opportunity after 5 years with the company Paid Parental Leave Daily lunches for in-office employees Monthly meal and tech allowances for remote employees Please note salary range is for Bay Area residents - we're still accepting remote applicants! We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
08/05/2026
Full time
Job Description Job Description At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles. Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously. That's why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner. Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry. Join us and help redefine what's possible as we shape the future of mobility. Role Summary: Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge. We are looking for a great Senior Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role, you will build and deploy AI models that analyze continuous data generated in the vehicle during the day-to-day operation, including system logs, traces, and vehicle internal signals (Ethernet and CAN) to detect and predict the health of different sub-systems and anticipate failures in real-time. You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization. You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle. You will be expected to collaborate with other leading developers who have a deep understanding and expertise of vehicle software and systems, and other AI developers working on MLOps and integration of AI models on vehicles expected to be on the road today. Expect to experiment with cutting-edge model architectures and best-in-class development tools. This is a hybrid role out of our Sunnyvale, CA, where you will be expected to work in our office 3 days a week. Responsibilities: Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities. Integrating ML flows, including cloud-based LLM APIs (Gemini, OpenAI, Claude), with emphasis on synthetic data creation. Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors. Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors. Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes. Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs. Apply quantization, pruning, distillation, and memory optimization to ensure models run within strict RAM/Flash budgets. Define the data strategy for on-device filtering: pre-processing on device and decide which data is processed locally versus processed in the cloud. Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI. Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. 10+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems. Proven experience mentoring junior engineers in software development. Expert Python (for training) and decent working knowledge of modern C++ (C+/17 for inference). Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM. Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs. Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data. Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment. Ability to communicate with stakeholders and articulate trade-offs. Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. Candidates with a strong Computer Vision (CV) / ADAS track record are highly encouraged to apply! Desired Skills: MS/PhD in Computer Science, Engineering, or related fields. Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT. Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. Experience with NVIDIA TensorRT, Qualcomm SNPE. Sunnyvale HQ Benefits & Perks Offered: Health care plan (Medical, Dental & Vision) Flexible and Dependent Care Expense program Retirement plan (401k) Life Insurance (Basic, Voluntary & AD&D) Unlimited paid time off per year, 14+ paid holidays Hybrid office work arrangement Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowance Phone & Internet reimbursement Computer Accessory Allowance The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for a base salary for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change. Base Salary Pay Range $227,000-$300,000 USD
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . Follow us on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Senior Software Engineer - Lifecycle Management will work collaboratively with a team to support medical device products from the transfer to production through product end of life. The Engineer will have a technical leadership role for supporting components and subassemblies of the body contouring products and will closely interact with a multi-disciplined Engineering team consisting of electrical, software and mechanical groups. The individual works within cross-functional teams and provides software requirements, design and implementation for current generation software and systems projects. He or she develops a thorough understanding of design requirements to ensure that the system's objectives are properly defined and ultimately achieved. This role is focused on continuous improvement of existing products. This individual must have strong technical skills complemented by great communications and teamwork qualities. Experience in a software development background in a structured/regulated environment such as medical device development is required. Responsibilities Lead and manage small scale projects for on time deliverable. Contribute to requirements definition at the functional level and work with cross functional groups. Perform in-depth data analysis and drive improvements to software or product quality. Design, develop, and support embedded, Windows embedded and desktop applications. Participate in software work product reviews/inspections. Interface, integrate, troubleshoot and debug software and hardware components. Generate required product development documentation including functional specifications and design documents. Execute manual or automated tests for verification and validation of software applications. Design, code and validate software tools for use in the verification and manufacturing of the product. Work with Software Verification, Product Support and Manufacturing to resolve software issues. Drive improvements to process quality. Responsible for performing all duties in compliance with FDA's Quality System Regulation (QSR), ISO13485, the Canadian Medical Device Regulations, and all other international regulatory requirements with which AbbVie complies. Qualifications BS in Software Engineering or equivalent degree and/or experience. Advanced degree desirable. Minimum of 8+ years experience in engineering design and at least 5 years of experience with embedded Windows programming with C# and . NET. At least 3 years of experience in medical devices or similarly controlled software environment preferred. Experience in developing event driven, multi-threaded Windows-based applications using .NET Framework and C# preferred. Required experience in structured software and systems development and integration, including experience in software design methodologies, design patterns, component-oriented software architecture to produce high-quality software applications. Experience with common protocols: RS232, SPI, USB a plus. Knowledge of PID control algorithm. Knowledge of software life cycle processes used in regulated development environments such as IEC 62304. Result-oriented, self-motivated and able to participate as both a team member and an individual contributor. Proficiency in MS Office, including Word and Excel. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html
08/05/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . Follow us on LinkedIn, Facebook, Instagram, X and YouTube. Job Description The Senior Software Engineer - Lifecycle Management will work collaboratively with a team to support medical device products from the transfer to production through product end of life. The Engineer will have a technical leadership role for supporting components and subassemblies of the body contouring products and will closely interact with a multi-disciplined Engineering team consisting of electrical, software and mechanical groups. The individual works within cross-functional teams and provides software requirements, design and implementation for current generation software and systems projects. He or she develops a thorough understanding of design requirements to ensure that the system's objectives are properly defined and ultimately achieved. This role is focused on continuous improvement of existing products. This individual must have strong technical skills complemented by great communications and teamwork qualities. Experience in a software development background in a structured/regulated environment such as medical device development is required. Responsibilities Lead and manage small scale projects for on time deliverable. Contribute to requirements definition at the functional level and work with cross functional groups. Perform in-depth data analysis and drive improvements to software or product quality. Design, develop, and support embedded, Windows embedded and desktop applications. Participate in software work product reviews/inspections. Interface, integrate, troubleshoot and debug software and hardware components. Generate required product development documentation including functional specifications and design documents. Execute manual or automated tests for verification and validation of software applications. Design, code and validate software tools for use in the verification and manufacturing of the product. Work with Software Verification, Product Support and Manufacturing to resolve software issues. Drive improvements to process quality. Responsible for performing all duties in compliance with FDA's Quality System Regulation (QSR), ISO13485, the Canadian Medical Device Regulations, and all other international regulatory requirements with which AbbVie complies. Qualifications BS in Software Engineering or equivalent degree and/or experience. Advanced degree desirable. Minimum of 8+ years experience in engineering design and at least 5 years of experience with embedded Windows programming with C# and . NET. At least 3 years of experience in medical devices or similarly controlled software environment preferred. Experience in developing event driven, multi-threaded Windows-based applications using .NET Framework and C# preferred. Required experience in structured software and systems development and integration, including experience in software design methodologies, design patterns, component-oriented software architecture to produce high-quality software applications. Experience with common protocols: RS232, SPI, USB a plus. Knowledge of PID control algorithm. Knowledge of software life cycle processes used in regulated development environments such as IEC 62304. Result-oriented, self-motivated and able to participate as both a team member and an individual contributor. Proficiency in MS Office, including Word and Excel. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html
Job Description Job Description About Us At Agtonomy, we're not just building tech-we're transforming how vital industries get work done. Our Physical AI and fleet services turn heavy machinery into intelligent, autonomous systems that tackle the toughest challenges in agriculture, turf, and beyond. Partnering with industry-leading equipment manufacturers, we're creating a future where labor shortages, environmental strain, and inefficiencies are relics of the past. Our team is a tight-knit group of bold thinkers-engineers, innovators, and industry experts-who thrive on turning audacious ideas into reality. If you want to shape the future of industries that matter, this is your shot. About the Role We're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments. You'll develop computer vision and machine learning systems that turns noisy camera and LiDAR data into robust 3D scene understanding - enabling heavy equipment to operate safely through dust, glare, occlusion, and whatever messy conditions a working site throws at it. The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception. You'll be at the center of that shift. This role is hands-on: you'll write production-grade software, distill and optimize models for embedded hardware, and validate your work on real machines at operating around the world. What You'll Do Develop real-time perception models for open-world obstacle and terrain understanding. Build multi-modal fusion that combines camera and LiDAR into a unified 3D/BEV representation, robust to occlusions, sensor degradation, and GNSS outages. Optimize models for low-latency inference on resource-constrained hardware, balancing accuracy and performance. Design auto-labeling pipelines that leverage foundation models and teacher-student distillation to scale labeling and close the loop from real-world field interventions. Design data and evaluation pipelines that curate large multi-sensor datasets and surface failures fast, with strong visualization and debugging tooling. Analyze performance metrics and iterate on algorithms to improve accuracy and efficiency of various perception subsystems. What You'll Bring A MS/PhD in Computer Science, AI, or a related field, or 6+ years of industry experience building vision-based perception systems. Deep expertise developing and deploying modern perception models: detection, segmentation, mono/stereo/metric depth, BEV/occupancy, sensor fusion, and 3D scene understanding. Fluency adapting, fine-tuning, and distilling large pre-trained vision and vision-language models. Strong grounding in multi-sensor integration (camera, LiDAR, radar): calibration, spatiotemporal sync, and cross-modal fusion. Experience handling large datasets efficiently and organizing them for labeling, training and evaluation. Fluency in Python with PyTorch/TensorFlow/OpenCV and the ability to write efficient, production-ready code for real-time systems. Proven ability to design experiments, analyze metrics (mAP, IoU, latency/throughput, and calibration/ECE), and optimize to meet stringent real-world performance and safety requirements. An eagerness to get your hands dirty and agility in a fast-moving, collaborative, small team environment with lots of ownership. What Makes You a Strong Fit Experience architecting multi-sensor ML systems from scratch. Experience building auto-labeling / data-engine flywheels at scale. Experience with compute-constrained pipelines including optimizing models to balance the accuracy vs. performance tradeoff, leveraging TensorRT, model quantization, etc. Familiarity with emerging predictive world models for anticipation, anomaly detection, or closed-loop simulation, and adjacent policy paradigms such as Vision-Language-Action (VLA) and World-Action (WAM) models. Experience with compute-constrained deployment: TensorRT, model quantization, and custom CUDA operations. Publications at top-tier perception/robotics venues (CVPR, ICRA, CoRL, RSS, etc.). Passion for how we feed, build, move, and maintain the world. The US base salary range for this full-time position is $200,000 to $280,000 + equity + benefits + unlimited PTO The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job-related skills, experience, and relevant education or specialty training. Your recruiter can share more about the specific salary range during the hiring process. Benefits • 100% covered medical, dental, and vision for the employee (partner, children, or family is additional) • Commuter Benefits • Flexible Spending Account (FSA or HSA) • Life Insurance • Short- and Long-Term Disability • 401k Plan • Stock Options • Collaborative work environment working alongside passionate mission-driven team!
08/05/2026
Full time
Job Description Job Description About Us At Agtonomy, we're not just building tech-we're transforming how vital industries get work done. Our Physical AI and fleet services turn heavy machinery into intelligent, autonomous systems that tackle the toughest challenges in agriculture, turf, and beyond. Partnering with industry-leading equipment manufacturers, we're creating a future where labor shortages, environmental strain, and inefficiencies are relics of the past. Our team is a tight-knit group of bold thinkers-engineers, innovators, and industry experts-who thrive on turning audacious ideas into reality. If you want to shape the future of industries that matter, this is your shot. About the Role We're looking for a skilled ML engineer to build the perception systems that give our autonomous machines human-like awareness in rugged, unstructured environments. You'll develop computer vision and machine learning systems that turns noisy camera and LiDAR data into robust 3D scene understanding - enabling heavy equipment to operate safely through dust, glare, occlusion, and whatever messy conditions a working site throws at it. The field is moving past bounding-box detection and hand-tuned tracking toward learned, dense scene representations, foundation-model-driven data engines, and uncertainty-aware perception. You'll be at the center of that shift. This role is hands-on: you'll write production-grade software, distill and optimize models for embedded hardware, and validate your work on real machines at operating around the world. What You'll Do Develop real-time perception models for open-world obstacle and terrain understanding. Build multi-modal fusion that combines camera and LiDAR into a unified 3D/BEV representation, robust to occlusions, sensor degradation, and GNSS outages. Optimize models for low-latency inference on resource-constrained hardware, balancing accuracy and performance. Design auto-labeling pipelines that leverage foundation models and teacher-student distillation to scale labeling and close the loop from real-world field interventions. Design data and evaluation pipelines that curate large multi-sensor datasets and surface failures fast, with strong visualization and debugging tooling. Analyze performance metrics and iterate on algorithms to improve accuracy and efficiency of various perception subsystems. What You'll Bring A MS/PhD in Computer Science, AI, or a related field, or 6+ years of industry experience building vision-based perception systems. Deep expertise developing and deploying modern perception models: detection, segmentation, mono/stereo/metric depth, BEV/occupancy, sensor fusion, and 3D scene understanding. Fluency adapting, fine-tuning, and distilling large pre-trained vision and vision-language models. Strong grounding in multi-sensor integration (camera, LiDAR, radar): calibration, spatiotemporal sync, and cross-modal fusion. Experience handling large datasets efficiently and organizing them for labeling, training and evaluation. Fluency in Python with PyTorch/TensorFlow/OpenCV and the ability to write efficient, production-ready code for real-time systems. Proven ability to design experiments, analyze metrics (mAP, IoU, latency/throughput, and calibration/ECE), and optimize to meet stringent real-world performance and safety requirements. An eagerness to get your hands dirty and agility in a fast-moving, collaborative, small team environment with lots of ownership. What Makes You a Strong Fit Experience architecting multi-sensor ML systems from scratch. Experience building auto-labeling / data-engine flywheels at scale. Experience with compute-constrained pipelines including optimizing models to balance the accuracy vs. performance tradeoff, leveraging TensorRT, model quantization, etc. Familiarity with emerging predictive world models for anticipation, anomaly detection, or closed-loop simulation, and adjacent policy paradigms such as Vision-Language-Action (VLA) and World-Action (WAM) models. Experience with compute-constrained deployment: TensorRT, model quantization, and custom CUDA operations. Publications at top-tier perception/robotics venues (CVPR, ICRA, CoRL, RSS, etc.). Passion for how we feed, build, move, and maintain the world. The US base salary range for this full-time position is $200,000 to $280,000 + equity + benefits + unlimited PTO The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job-related skills, experience, and relevant education or specialty training. Your recruiter can share more about the specific salary range during the hiring process. Benefits • 100% covered medical, dental, and vision for the employee (partner, children, or family is additional) • Commuter Benefits • Flexible Spending Account (FSA or HSA) • Life Insurance • Short- and Long-Term Disability • 401k Plan • Stock Options • Collaborative work environment working alongside passionate mission-driven team!
Job Description Job Description Orchard Robotics is a Series A startup backed by top VCs like Quiet Capital, Shine Capital, and General Catalyst. We're securing America's food supply by building the AI farmer that automates our nation's farms. We've raised over $25M in pursuit of our mission to help farmers farm more profitably and sustainably than ever before. What We Do: We start by collecting the most valuable data for farmers, telling them everything about what is growing on their millions of trees, across thousands of acres of farmland. We do this using advanced camera systems we build, that take pictures of every one of the billions of fruit in a farm. This data lives in our cloud data platform, FruitScope, that we've developed from the ground up to help farmers manage their crops with precision. Farmers across the nation use our industry-leading software to look at their data, make critical decisions, and command farming operations on a daily basis. Our technology is used today across some of the largest farms in the nation. The Role: In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing. We are looking for a Senior Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems. About the role: As an early engineer, you'll receive generous equity compensation Full-time role at our San Francisco, CA office Flexible working hours Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium We move fast, and sometimes this means staying late or working weekends Our team is close-knit & highly driven, you'll work directly with our CEO and entire team We're deeply motivated by the impact we're making - every line of code written or new system built means less food that goes to waste, and more people who are fed. What you'll do: Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms. Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems. Develop, deploy, and monitor infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices. Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance. Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems. Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features. Be a generalist, supporting different parts of our software stack as needed. What makes you a good fit: 5+ years of experience building production-grade data pipelines and ML infrastructure. Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). Strong experience with data engineering tools (e.g., Pandas, SQL, Apache Airflow, Spark). Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Experience working with massive amounts of real-world training data. Familiarity with MLops software and data engineering to ensure consistent deployment of ML models. Ability to work independently, learn quickly, and operate in a dynamic environment Enthusiasm for taking on multiple roles and responsibilities as our company grows. Bonus Points: Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson Experience prototyping, evaluating, or deploying new ML/CV models on the edge. If you're looking to help make a positive impact in the world by building the future of farming, come join us! Compensation Range: $150K - $265K
08/05/2026
Full time
Job Description Job Description Orchard Robotics is a Series A startup backed by top VCs like Quiet Capital, Shine Capital, and General Catalyst. We're securing America's food supply by building the AI farmer that automates our nation's farms. We've raised over $25M in pursuit of our mission to help farmers farm more profitably and sustainably than ever before. What We Do: We start by collecting the most valuable data for farmers, telling them everything about what is growing on their millions of trees, across thousands of acres of farmland. We do this using advanced camera systems we build, that take pictures of every one of the billions of fruit in a farm. This data lives in our cloud data platform, FruitScope, that we've developed from the ground up to help farmers manage their crops with precision. Farmers across the nation use our industry-leading software to look at their data, make critical decisions, and command farming operations on a daily basis. Our technology is used today across some of the largest farms in the nation. The Role: In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing. We are looking for a Senior Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems. About the role: As an early engineer, you'll receive generous equity compensation Full-time role at our San Francisco, CA office Flexible working hours Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium We move fast, and sometimes this means staying late or working weekends Our team is close-knit & highly driven, you'll work directly with our CEO and entire team We're deeply motivated by the impact we're making - every line of code written or new system built means less food that goes to waste, and more people who are fed. What you'll do: Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms. Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems. Develop, deploy, and monitor infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices. Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance. Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems. Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features. Be a generalist, supporting different parts of our software stack as needed. What makes you a good fit: 5+ years of experience building production-grade data pipelines and ML infrastructure. Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). Strong experience with data engineering tools (e.g., Pandas, SQL, Apache Airflow, Spark). Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Experience working with massive amounts of real-world training data. Familiarity with MLops software and data engineering to ensure consistent deployment of ML models. Ability to work independently, learn quickly, and operate in a dynamic environment Enthusiasm for taking on multiple roles and responsibilities as our company grows. Bonus Points: Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson Experience prototyping, evaluating, or deploying new ML/CV models on the edge. If you're looking to help make a positive impact in the world by building the future of farming, come join us! Compensation Range: $150K - $265K
Job Description Job Description Associate Computer Vision & Machine Learning for Autonomous Anti-Drone Systems Company Overview: Allen Control Systems (ACS) is a cutting-edge defense startup, founded by two ex-Navy electrical engineers with a proven track record in robotics and software. We are developing a small, autonomous gun turret that employs advanced computer vision and control systems to precisely target and neutralize small drones and loitering munitions. Our innovative approach requires overcoming significant technical challenges, making this an exciting and dynamic environment for experienced engineers. With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous venture acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. We're hiring across multiple experience levels, including: Associate CV/ML Engineer CV/ML Engineer Senior CV/ML Engineer Staff CV/ML Engineer Senior Staff CV/ML Engineer Your title and level will be determined based on your experience, skills, and the scope of responsibility appropriate for the role. What You'll Do: Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification. Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability. Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture. Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions. Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges. What You'll Need: Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career. At least a Bachelor's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision. 0-3+ years of experience working on machine-learning-based computer vision, ideally in the context of robotics. A proven track record of developing and deploying computer vision systems, ideally in real-time or safety-critical applications. Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. Experience with embedded systems and integrating computer vision algorithms into hardware. Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems. You enjoy collaborating with other engineers to solve complex technical challenges. What We Offer: Competitive salary ACS Equity Package Health, Dental, Vision Insurance Paid Time Off Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Compensation Range: $94K - $154K
08/05/2026
Full time
Job Description Job Description Associate Computer Vision & Machine Learning for Autonomous Anti-Drone Systems Company Overview: Allen Control Systems (ACS) is a cutting-edge defense startup, founded by two ex-Navy electrical engineers with a proven track record in robotics and software. We are developing a small, autonomous gun turret that employs advanced computer vision and control systems to precisely target and neutralize small drones and loitering munitions. Our innovative approach requires overcoming significant technical challenges, making this an exciting and dynamic environment for experienced engineers. With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous venture acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. We're hiring across multiple experience levels, including: Associate CV/ML Engineer CV/ML Engineer Senior CV/ML Engineer Staff CV/ML Engineer Senior Staff CV/ML Engineer Your title and level will be determined based on your experience, skills, and the scope of responsibility appropriate for the role. What You'll Do: Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification. Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability. Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture. Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions. Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges. What You'll Need: Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career. At least a Bachelor's degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision. 0-3+ years of experience working on machine-learning-based computer vision, ideally in the context of robotics. A proven track record of developing and deploying computer vision systems, ideally in real-time or safety-critical applications. Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. Experience with embedded systems and integrating computer vision algorithms into hardware. Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems. You enjoy collaborating with other engineers to solve complex technical challenges. What We Offer: Competitive salary ACS Equity Package Health, Dental, Vision Insurance Paid Time Off Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Compensation Range: $94K - $154K
Job Description Job Description Senior Computer Vision & Machine Learning Engineer for Autonomous Anti-Drone Systems Company Overview: Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy electrical engineers with a proven track record in robotics and software. We are developing an autonomous gun turret using advanced computer vision and control systems to precisely detect, track, and neutralize enemy drones. With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous venture acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. About The Role: We are looking for a Senior Level Computer Vision and Machine Learning Engineer to develop and optimize the CV/ML systems at the core of our autonomous gun turret, with a focus on real-time drone detection, tracking, and classification. You will work closely with electrical engineers to integrate vision systems into the turret's hardware architecture and contribute to hardening the prototype into a military-grade system. What You'll Do: Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification. Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability. Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture. Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions. Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges. What You'll Need: Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career. More than 7+ years of experience working on machine-learning-based computer vision, ideally in the context of robotics. At least a Bachelors and/or Masters Degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision. A proven track record of senior-level experience developing and deploying computer vision systems, ideally in real-time or safety-critical applications. Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. Experience with embedded systems and integrating computer vision algorithms into hardware. Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems. You enjoy collaborating with other engineers to solve complex technical challenges. What We Offer: Competitive salary ACS Equity Package Health, Dental, Vision Insurance Paid Time Off Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Compensation Range: $163K - $261K
08/05/2026
Full time
Job Description Job Description Senior Computer Vision & Machine Learning Engineer for Autonomous Anti-Drone Systems Company Overview: Allen Control Systems (ACS) is a cutting-edge defense startup founded by two former Navy electrical engineers with a proven track record in robotics and software. We are developing an autonomous gun turret using advanced computer vision and control systems to precisely detect, track, and neutralize enemy drones. With an engineering-first culture, ACS values technical excellence and innovation. Backed by our founders' successful exits from two previous venture acquired for a combined $180M in 2022, we are committed to ensuring that the groundbreaking technologies we develop will have a real-world impact. About The Role: We are looking for a Senior Level Computer Vision and Machine Learning Engineer to develop and optimize the CV/ML systems at the core of our autonomous gun turret, with a focus on real-time drone detection, tracking, and classification. You will work closely with electrical engineers to integrate vision systems into the turret's hardware architecture and contribute to hardening the prototype into a military-grade system. What You'll Do: Development and optimization of computer vision algorithms for our autonomous gun turret, focusing on real-time drone detection, tracking, and classification. Design and implement machine learning models that can operate in resource-constrained environments while maintaining high accuracy and reliability. Collaborate closely with electrical engineers to integrate computer vision systems into the turret's hardware architecture. Conduct extensive testing and validation of computer vision algorithms in various scenarios to ensure robustness and performance under different environmental conditions. Contribute to the hardening of the prototype turret into a military-grade system, and assist in developing variants for different weapon systems and engagement ranges. What You'll Need: Deep passion for machine learning, computer vision, and robotics, and have been exploring these areas since early in your career. More than 7+ years of experience working on machine-learning-based computer vision, ideally in the context of robotics. At least a Bachelors and/or Masters Degree in Computer Science, Electrical Engineering, or a related field, with a strong focus on machine learning and computer vision. A proven track record of senior-level experience developing and deploying computer vision systems, ideally in real-time or safety-critical applications. Proficient in Python, C++, and have experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. Experience with embedded systems and integrating computer vision algorithms into hardware. Familiar with various sensors (e.g., cameras, LIDAR, RADAR) and their integration into autonomous systems. You enjoy collaborating with other engineers to solve complex technical challenges. What We Offer: Competitive salary ACS Equity Package Health, Dental, Vision Insurance Paid Time Off Allen Control Systems is an Equal Opportunity Employer, providing equal employment opportunities to all employees and applicants for employment. Allen Control Systems prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Compensation Range: $163K - $261K
Job Description Job Description Location Algorithm Engineer Location: Belmont, CA (hybrid) Employees : Industry : Wireless services Position Reporting To: Principal Engineer Dynamic Bay Area startup is seeking a Wireless Location Algorithm Engineer tasked with designing, optimizing, and implementing advanced signal processing techniques and location estimation algorithms. This work will help determine the real-time positioning of devices in dynamic environments. Most Important Responsibilities : Develop algorithms to extract highly accurate timing and spatial data from wireless signals in complex environments. Create both physical and virtual test setups to assess system components and ensure their performance in controlled scenarios. Acquire in-depth knowledge of operating principles and actively contribute to knowledge sharing within the team. Continuously analyze and improve existing location estimation methodologies, adapting them to meet the latest industry trends and standards. Required Experience and Skills : PhD in Electrical Engineering, or equivalent research experience, specializing in wireless communications. 3+ years of industry experience in location based wireless engineering. Comprehensive knowledge of wireless communication systems and protocols, particularly those in the IEEE 802.11 series. Expertise in wireless channel modeling and the effective use of Channel State Information (CSI). Familiarity with key concepts like modulation schemes, coding techniques, spatial stream diversity, cyclic shift diversity, multipath interference, beamforming, and angle of arrival. In-depth understanding of Time Difference of Arrival (TDoA) and other location-based techniques. Solid grounding in time synchronization techniques and their practical applications. Proficiency in Linux-based development environments and command-line tools. Strong programming skills in Python, with hands-on experience using libraries such as NumPy. Familiarity with version control, particularly GIT. Adherence to best practices in software development, including modular design, interface abstraction, unit testing, and managing version compatibility. Preferred Skills : Knowledge of RF certification bodies and understanding of relevant regulatory standards. Practical experience with RF hardware design or system interfacing. Background in modeling uncertainty in complex systems. Exposure to machine learning techniques in Python, including GPU optimization. Experience with adaptive filtering techniques. Expertise with adaptive filtering techniques. Expertise in modeling 3D wireless channels using ray tracing or similar advanced methods. Advanced Python skills, including classes, asynchronous programming, and list comprehensions. Experience with embedded systems or real-time programming environments. Proficiency in MATLAB for simulation and modeling purposes. Featured Benefits: Medical, Vision, Dental, Stock Options Compensation: $150 - $190K + Stock Options
08/05/2026
Full time
Job Description Job Description Location Algorithm Engineer Location: Belmont, CA (hybrid) Employees : Industry : Wireless services Position Reporting To: Principal Engineer Dynamic Bay Area startup is seeking a Wireless Location Algorithm Engineer tasked with designing, optimizing, and implementing advanced signal processing techniques and location estimation algorithms. This work will help determine the real-time positioning of devices in dynamic environments. Most Important Responsibilities : Develop algorithms to extract highly accurate timing and spatial data from wireless signals in complex environments. Create both physical and virtual test setups to assess system components and ensure their performance in controlled scenarios. Acquire in-depth knowledge of operating principles and actively contribute to knowledge sharing within the team. Continuously analyze and improve existing location estimation methodologies, adapting them to meet the latest industry trends and standards. Required Experience and Skills : PhD in Electrical Engineering, or equivalent research experience, specializing in wireless communications. 3+ years of industry experience in location based wireless engineering. Comprehensive knowledge of wireless communication systems and protocols, particularly those in the IEEE 802.11 series. Expertise in wireless channel modeling and the effective use of Channel State Information (CSI). Familiarity with key concepts like modulation schemes, coding techniques, spatial stream diversity, cyclic shift diversity, multipath interference, beamforming, and angle of arrival. In-depth understanding of Time Difference of Arrival (TDoA) and other location-based techniques. Solid grounding in time synchronization techniques and their practical applications. Proficiency in Linux-based development environments and command-line tools. Strong programming skills in Python, with hands-on experience using libraries such as NumPy. Familiarity with version control, particularly GIT. Adherence to best practices in software development, including modular design, interface abstraction, unit testing, and managing version compatibility. Preferred Skills : Knowledge of RF certification bodies and understanding of relevant regulatory standards. Practical experience with RF hardware design or system interfacing. Background in modeling uncertainty in complex systems. Exposure to machine learning techniques in Python, including GPU optimization. Experience with adaptive filtering techniques. Expertise with adaptive filtering techniques. Expertise in modeling 3D wireless channels using ray tracing or similar advanced methods. Advanced Python skills, including classes, asynchronous programming, and list comprehensions. Experience with embedded systems or real-time programming environments. Proficiency in MATLAB for simulation and modeling purposes. Featured Benefits: Medical, Vision, Dental, Stock Options Compensation: $150 - $190K + Stock Options
We are seeking an experienced Principal or Senior Embedded Software Engineer to design and develop embedded software for space-based systems, including computer boards. This is a hands-on, on-site position focused on real-time, high-reliability applications.
08/05/2026
Full time
We are seeking an experienced Principal or Senior Embedded Software Engineer to design and develop embedded software for space-based systems, including computer boards. This is a hands-on, on-site position focused on real-time, high-reliability applications.
Description: Design, develop, test, and optimize embedded software solutions for GNSS navigation systems. Develop and implement complex GNSS navigation algorithms and estimation techniques using C/C++. Create engineering designs, technical specifications, validation plans, and software documentation. Perform software testing, peer reviews, debugging, and continuous improvement of embedded systems. Collaborate with cross-functional teams to diagnose issues and deliver high-quality software features. Develop engineering standards and ensure compliance with quality, safety, and regulatory requirements. Support project planning, risk management, and technical execution throughout the product lifecycle. Contribute to process improvements, engineering innovation, and embedded software best practices.
08/05/2026
Full time
Description: Design, develop, test, and optimize embedded software solutions for GNSS navigation systems. Develop and implement complex GNSS navigation algorithms and estimation techniques using C/C++. Create engineering designs, technical specifications, validation plans, and software documentation. Perform software testing, peer reviews, debugging, and continuous improvement of embedded systems. Collaborate with cross-functional teams to diagnose issues and deliver high-quality software features. Develop engineering standards and ensure compliance with quality, safety, and regulatory requirements. Support project planning, risk management, and technical execution throughout the product lifecycle. Contribute to process improvements, engineering innovation, and embedded software best practices.
JT4, LLC provides engineering and technical support to multiple western test ranges for the U.S. Air Force, Space Force, and Navy under the Joint Range Technical Services Contract, better known as J-Tech II. JT4 develops and maintains realistic, integrated test and training environments and prepares our nation's war-fighting aircraft, weapons systems, and aircrews for today's missions and tomorrow's global challenges. Job Summary Essential Functions/Duties Under minimal supervision, converts and oversees conversion of data from project specifications and statement of problem and procedures to create or modify computer programs requiring and applying advanced knowledge of programming techniques and computer system. Employee will be responsible for the following functions/duties: Prepares flowcharts and diagrams to illustrate a sequence of steps that a program must follow and to describe logical operations involved Converts project specifications into a sequence of detailed instructions and logical steps for coding into a language readable by computers, applying knowledge of computer programming techniques and computer languages Designs and writes basic to moderately complex computer programs Uses computer-aided software tools, such as flowchart design and code generation, in each stage of system development Operates computer system to check out programs, troubleshoot and test systems Monitors performance of programs after implementation Analyzes, reviews, and alters computer programs to increase operating efficiency or to adapt to new requirements Prepares documentation to describe program development, logic, coding, and corrections Develops user manuals to describe installation and operating procedures Provides technical assistance to program users as required Provides work direction to subordinate department employees and may occasionally function as a work group lead Performs related work as required. Desired Qualifications Core Engineering: C# (Full Stack). Solid understanding of Object-Oriented Programming (OOP), principles, and design patterns. Adjacent OOP languages such as Java, C++, or Python is a significant plus. Modern .NET (e.g., .NET 6/8+). Windows Presentation Foundation (WPF) and MVVM patterns. Fluency in IP transport (TCP, UDP) network communication, socket programming, domains, subnetting, and network design of simple topologies. Secondary languages and frameworks including Python (especially for mathematical/data processing), WinForms, Delphi, and Fortran are a plus. Embedded Software Development experience utilizing LabVIEW for cRIO, cDAQ targets is a significant plus. Modern embedded languages like Rust or Real-Time Operating Systems (RTOS) is a significant plus. Version Control Proficiency in the use of Git (GitLab, GitHub). Requirements Education, Technical, and Work Experience Bachelor's Degree in Computer Programming; or equivalent technical training from an accredited academic institution, completion of a recognized certification program, or equivalent experience and demonstrated skills, knowledge, and technical competence in computer programming. Possess nine (9) years of additional related experience. Must have demonstrated proficiency with required computer languages and have a good understanding of computer systems including networks, servers, and personal computer. In addition, a Computer Programmer must possess the following qualifications: Must possess planning and organizing skills and be able to work under deadlines Must possess verbal and written communication skills sufficient to permit interaction with other employees as well as taking work direction from senior Programmers or Supervisors Must qualify for and maintain a government security clearance Must possess a valid, state-issued driver's license. Must be a U.S. citizen. Benefits Medical, Dental, Vision Insurance Benefits Active on Day 1 Life Insurance Health Savings Accounts/FSA's Disability Insurance Paid Time Off 401(k) Plan Options with Employer Match JT4 will match 50%, up to an 8% contribution 100% Immediate Vesting Tuition Reimbursement Other Responsibilities Each employee must read, understand, and implement the general and specific operational, safety, quality, and environmental requirements of all plans, procedures, and policies pertaining to their job. Working Conditions Typical office environment with no unusual hazards, occasional lifting (up to 20 pounds), constant sitting while using the computer terminal, constant use of sight abilities while reviewing documents, constant use of speech/hearing abilities for communication, and constant mental alertness. Travel to remote locations will be required. Disclaimer The above statements are intended to describe the general nature and level of work being performed by personnel assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills required of persons so classified. Tasking is in support of a federal government contract that requires U.S. citizenship. This job requires a candidate to be eligible for a government security clearance, state-issued driver's license or other licenses / certifications and the inability to obtain and maintain the required clearance, license or certification may affect an employee's ability to maintain employment. SCC: JSD12; A3UTTR
08/05/2026
Full time
JT4, LLC provides engineering and technical support to multiple western test ranges for the U.S. Air Force, Space Force, and Navy under the Joint Range Technical Services Contract, better known as J-Tech II. JT4 develops and maintains realistic, integrated test and training environments and prepares our nation's war-fighting aircraft, weapons systems, and aircrews for today's missions and tomorrow's global challenges. Job Summary Essential Functions/Duties Under minimal supervision, converts and oversees conversion of data from project specifications and statement of problem and procedures to create or modify computer programs requiring and applying advanced knowledge of programming techniques and computer system. Employee will be responsible for the following functions/duties: Prepares flowcharts and diagrams to illustrate a sequence of steps that a program must follow and to describe logical operations involved Converts project specifications into a sequence of detailed instructions and logical steps for coding into a language readable by computers, applying knowledge of computer programming techniques and computer languages Designs and writes basic to moderately complex computer programs Uses computer-aided software tools, such as flowchart design and code generation, in each stage of system development Operates computer system to check out programs, troubleshoot and test systems Monitors performance of programs after implementation Analyzes, reviews, and alters computer programs to increase operating efficiency or to adapt to new requirements Prepares documentation to describe program development, logic, coding, and corrections Develops user manuals to describe installation and operating procedures Provides technical assistance to program users as required Provides work direction to subordinate department employees and may occasionally function as a work group lead Performs related work as required. Desired Qualifications Core Engineering: C# (Full Stack). Solid understanding of Object-Oriented Programming (OOP), principles, and design patterns. Adjacent OOP languages such as Java, C++, or Python is a significant plus. Modern .NET (e.g., .NET 6/8+). Windows Presentation Foundation (WPF) and MVVM patterns. Fluency in IP transport (TCP, UDP) network communication, socket programming, domains, subnetting, and network design of simple topologies. Secondary languages and frameworks including Python (especially for mathematical/data processing), WinForms, Delphi, and Fortran are a plus. Embedded Software Development experience utilizing LabVIEW for cRIO, cDAQ targets is a significant plus. Modern embedded languages like Rust or Real-Time Operating Systems (RTOS) is a significant plus. Version Control Proficiency in the use of Git (GitLab, GitHub). Requirements Education, Technical, and Work Experience Bachelor's Degree in Computer Programming; or equivalent technical training from an accredited academic institution, completion of a recognized certification program, or equivalent experience and demonstrated skills, knowledge, and technical competence in computer programming. Possess nine (9) years of additional related experience. Must have demonstrated proficiency with required computer languages and have a good understanding of computer systems including networks, servers, and personal computer. In addition, a Computer Programmer must possess the following qualifications: Must possess planning and organizing skills and be able to work under deadlines Must possess verbal and written communication skills sufficient to permit interaction with other employees as well as taking work direction from senior Programmers or Supervisors Must qualify for and maintain a government security clearance Must possess a valid, state-issued driver's license. Must be a U.S. citizen. Benefits Medical, Dental, Vision Insurance Benefits Active on Day 1 Life Insurance Health Savings Accounts/FSA's Disability Insurance Paid Time Off 401(k) Plan Options with Employer Match JT4 will match 50%, up to an 8% contribution 100% Immediate Vesting Tuition Reimbursement Other Responsibilities Each employee must read, understand, and implement the general and specific operational, safety, quality, and environmental requirements of all plans, procedures, and policies pertaining to their job. Working Conditions Typical office environment with no unusual hazards, occasional lifting (up to 20 pounds), constant sitting while using the computer terminal, constant use of sight abilities while reviewing documents, constant use of speech/hearing abilities for communication, and constant mental alertness. Travel to remote locations will be required. Disclaimer The above statements are intended to describe the general nature and level of work being performed by personnel assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties, and skills required of persons so classified. Tasking is in support of a federal government contract that requires U.S. citizenship. This job requires a candidate to be eligible for a government security clearance, state-issued driver's license or other licenses / certifications and the inability to obtain and maintain the required clearance, license or certification may affect an employee's ability to maintain employment. SCC: JSD12; A3UTTR
Job Title: Embedded Software Engineer (Sr Levels) Department: Engineering Reports To: Director of Engineering FLSA Status: Exempt Job Summary Vanteon is seeking a Principal Embedded Software Engineer to join our team. The position will design and develop Petalinux Board Support Package and MAC layer communications firmware for custom hardware. Specific platforms would include the AMD/Xilinx Zynq ARM and ADI ADRV900X Transceiver platforms. Duties/Responsibilities The following is a list of expected duties to be involved in this position; this is not fully inclusive, and management may assign other duties: Analyze system for identification of use cases and development of System Requirement Specifications. Design and implement embedded software, device drivers, and board support packages. Investigate and propose project-related technologies to meet requirements. Create technical documentation including Software Requirements Specifications, Design Documents, Test Summary Reports, and development notes. Collaborate with hardware and other engineers for design and integration efforts. Define and execute engineering verification and acceptance criteria tests. Mentor more junior engineers. Supervisory Responsibilities None Required Skills & Knowledge Embedded systems software for real-time bare-metal, RTOSs, and embedded Linux-based systems. Multi-threaded programming, distributed design, device driver development, and hardware-level. diagnostics, MAC sublayer, BIOS / Bootloader development and configuration, and interrupt handling. BSP creation and new custom hardware bring-up for bare-metal, RTOS, and embedded Linux platforms. Proficient with C/C++ and able to work at the assembly level for embedded processors. Advanced object-oriented design approaches to reusable software systems design. Experience using embedded tools such as compilers, debuggers, ICE, and emulators. Experience with common build management systems (make, etc.) and git version control systems. Hardware/software interface design experience (SPI, I2C, LVDS, DMA, etc.). Proven track record of successful product completion and deployment. Excellent written and verbal communication and analytical skills. Highly motivated, well-organized self-starter. Desired Skills AMD/Xilinx FPGA HDL, hardware configuration, and block design familiarity. AMD/Xilinx Petalinux/Yocto bring-up, customization, and Zynq hardware integration. ADI ADRV9002 configuration and control. Experience with Python for testing standardization, automation, and test fixturing. Linux Yocto build recipes. Linux kernel and application software development. Linux Ethernet driver stack configuration and routing (OpenWRT, etc.). Experience with common CI/CD tools and containerize development methodologies. Experience with UML design modeling and tools. Secure Bootloaders, Binary Signing and Encryption, and TPM integrations. OpenAmp Education and Experience BS EE/CE/CS/SE 5+ years' experience in embedded systems software Other Requirements Training and regular duties require a physical office presence. Although Vanteon will comply with all NYS/Federal requirements related to COVID-19, candidates will be expected to work on-site. Although minimal, some circumstances may require a weekly commitment above 40 hours or hours outside of regular business hours. Physical Requirements Prolonged periods sitting at a desk and working on a computer Be able to perform low to moderately strenuous physical activities requiring standing, walking, and reaching. Must be able to lift up to 15 pounds at times. The physical demands described above represent those that an employee must meet to perform the essential functions of this job successfully. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Equal Opportunity Employer Vanteon Corporation provides equal employment opportunities to all employees and applicants for employment. It prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Compensation Range A candidate's compensation will depend heavily on their skills and experience and will include a very competitive benefits package. Position is eligible for a variety of bonuses, including client referrals, employee referrals, publications, and extra effort. The estimated range for specific positions associated with this job posting is: Principal Engineer - $115,000 to $135,000 Senior Principal Engineer - $130,000 to $150,000 Applying Applicants should submit a resume and cover letter to Ronnie Ells - . Please note that all offers for hire are contingent on passing e-verify, background, and drug screenings. In addition, you must be able to work with ITAR and CUI data. About Vanteon Vanteon LLC, a wholly owned subsidiary of Performance Drone Works, is an engineering services company specializing in wireless and RF design. We offer Analog, Digital, RF, Hardware, Software, and FPGA design services. At Vanteon, we develop products for companies that range from small start-ups to large Fortune 50 companies. The designs we create include Software-Defined Radio (SDR), Wi-Fi, Bluetooth, etc., for markets such as telecom (3G, 4G, 5G cellular), Aviation, Medical, Government, Industrial, and more. Types of projects include handheld devices, wearables, RADAR, signal/spectrum analyzers, and wireless widgets of all kinds. Vanteon has been voted one of the "Best Companies to Work for in NY" for 15 years running; most times, we've ranked in the top 5.
08/05/2026
Full time
Job Title: Embedded Software Engineer (Sr Levels) Department: Engineering Reports To: Director of Engineering FLSA Status: Exempt Job Summary Vanteon is seeking a Principal Embedded Software Engineer to join our team. The position will design and develop Petalinux Board Support Package and MAC layer communications firmware for custom hardware. Specific platforms would include the AMD/Xilinx Zynq ARM and ADI ADRV900X Transceiver platforms. Duties/Responsibilities The following is a list of expected duties to be involved in this position; this is not fully inclusive, and management may assign other duties: Analyze system for identification of use cases and development of System Requirement Specifications. Design and implement embedded software, device drivers, and board support packages. Investigate and propose project-related technologies to meet requirements. Create technical documentation including Software Requirements Specifications, Design Documents, Test Summary Reports, and development notes. Collaborate with hardware and other engineers for design and integration efforts. Define and execute engineering verification and acceptance criteria tests. Mentor more junior engineers. Supervisory Responsibilities None Required Skills & Knowledge Embedded systems software for real-time bare-metal, RTOSs, and embedded Linux-based systems. Multi-threaded programming, distributed design, device driver development, and hardware-level. diagnostics, MAC sublayer, BIOS / Bootloader development and configuration, and interrupt handling. BSP creation and new custom hardware bring-up for bare-metal, RTOS, and embedded Linux platforms. Proficient with C/C++ and able to work at the assembly level for embedded processors. Advanced object-oriented design approaches to reusable software systems design. Experience using embedded tools such as compilers, debuggers, ICE, and emulators. Experience with common build management systems (make, etc.) and git version control systems. Hardware/software interface design experience (SPI, I2C, LVDS, DMA, etc.). Proven track record of successful product completion and deployment. Excellent written and verbal communication and analytical skills. Highly motivated, well-organized self-starter. Desired Skills AMD/Xilinx FPGA HDL, hardware configuration, and block design familiarity. AMD/Xilinx Petalinux/Yocto bring-up, customization, and Zynq hardware integration. ADI ADRV9002 configuration and control. Experience with Python for testing standardization, automation, and test fixturing. Linux Yocto build recipes. Linux kernel and application software development. Linux Ethernet driver stack configuration and routing (OpenWRT, etc.). Experience with common CI/CD tools and containerize development methodologies. Experience with UML design modeling and tools. Secure Bootloaders, Binary Signing and Encryption, and TPM integrations. OpenAmp Education and Experience BS EE/CE/CS/SE 5+ years' experience in embedded systems software Other Requirements Training and regular duties require a physical office presence. Although Vanteon will comply with all NYS/Federal requirements related to COVID-19, candidates will be expected to work on-site. Although minimal, some circumstances may require a weekly commitment above 40 hours or hours outside of regular business hours. Physical Requirements Prolonged periods sitting at a desk and working on a computer Be able to perform low to moderately strenuous physical activities requiring standing, walking, and reaching. Must be able to lift up to 15 pounds at times. The physical demands described above represent those that an employee must meet to perform the essential functions of this job successfully. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Equal Opportunity Employer Vanteon Corporation provides equal employment opportunities to all employees and applicants for employment. It prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Compensation Range A candidate's compensation will depend heavily on their skills and experience and will include a very competitive benefits package. Position is eligible for a variety of bonuses, including client referrals, employee referrals, publications, and extra effort. The estimated range for specific positions associated with this job posting is: Principal Engineer - $115,000 to $135,000 Senior Principal Engineer - $130,000 to $150,000 Applying Applicants should submit a resume and cover letter to Ronnie Ells - . Please note that all offers for hire are contingent on passing e-verify, background, and drug screenings. In addition, you must be able to work with ITAR and CUI data. About Vanteon Vanteon LLC, a wholly owned subsidiary of Performance Drone Works, is an engineering services company specializing in wireless and RF design. We offer Analog, Digital, RF, Hardware, Software, and FPGA design services. At Vanteon, we develop products for companies that range from small start-ups to large Fortune 50 companies. The designs we create include Software-Defined Radio (SDR), Wi-Fi, Bluetooth, etc., for markets such as telecom (3G, 4G, 5G cellular), Aviation, Medical, Government, Industrial, and more. Types of projects include handheld devices, wearables, RADAR, signal/spectrum analyzers, and wireless widgets of all kinds. Vanteon has been voted one of the "Best Companies to Work for in NY" for 15 years running; most times, we've ranked in the top 5.
Job Description: We are seeking a Senior Software Engineer contractor to develop robotics platform software on NVIDIA Jetson (Linux/ROS2) for a manipulation system integrating custom grippers, sensors, and actuator subsystems. You will write ROS2 nodes, develop host-side SDKs interfacing with embedded hardware over Ethernet and EtherCAT, integrate sensor pipelines (cameras, depth, tactile, IMU), and deploy perception/control algorithms into the real-time platform. The work is hands-on, systems-level C++/Python on Ubuntu with PREEMPT_RT, JetPack, and Docker.
08/05/2026
Full time
Job Description: We are seeking a Senior Software Engineer contractor to develop robotics platform software on NVIDIA Jetson (Linux/ROS2) for a manipulation system integrating custom grippers, sensors, and actuator subsystems. You will write ROS2 nodes, develop host-side SDKs interfacing with embedded hardware over Ethernet and EtherCAT, integrate sensor pipelines (cameras, depth, tactile, IMU), and deploy perception/control algorithms into the real-time platform. The work is hands-on, systems-level C++/Python on Ubuntu with PREEMPT_RT, JetPack, and Docker.