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 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 The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. As part of the global research organization, our AI research in Silicon Valley focuses on Foundation Models and Gen AI, Human-AI Collaboration and Trustworthy AI, AI for Advanced Driver-Assistance Systems (ADAS) and Autonomous Systems, AI Systems Engineering, and Industry AI. We develop scalable, intelligent, and trustworthy AI solutions to enable inspiring user experiences for Bosch products and services in application areas such as ADAS, smart manufacturing, enterprise AI, healthcare, smart home, and building solutions. Originating from Bosch AI research in Silicon Valley, our Vision and Language AI Group advances cutting-edge research in two core AI areas: large language models (LLMs) and 3D computer vision. In the LLM space, we focus on AI agents, retrieval-augmented generation, and effective adaptation of LLMs to Bosch domain-specific applications. In 3D vision, we advance spatial intelligence with 3D world models that perceive, reconstruct, and simulate the physical world, enabling reliable embodied control and sim-to-real transfer. By integrating these two areas, we aim to build intelligent systems that can perceive, reason, and communicate seamlessly across both language and spatial environments. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals such as ACL, EMNLP, CVPR, ICCV, ECCV, NeurIPS, AAAI and CoRL. Job Description Responsibilities: Design, build, and evaluate agentic AI systems that can plan, reason, act, and collaborate across tools and environments, including single- and multi-agent setups for complex, long-horizon tasks. Develop robust agent harnesses and evaluation frameworks covering end-to-end testing, regression analysis, trace logging, replayability, and metrics for success, cost, latency, robustness, and safety. Implement self-improving agent loops using reflection, critique, self-debugging, and iterative optimization strategies driven by agent experience, execution traces, and automated feedback. Architect and optimize agent memory systems, including short-term and long-term memory, retrieval-augmented generation, summarization, compression, forgetting policies, and privacy-aware retention. Enable reliable deployment of agents on constrained and edge environments, focusing on model/runtime optimization, partial or offline execution, secure tool-use, and seamless edge-cloud coordination. Qualifications Basic Qualifications Bachelor or master's degree in computer science or engineering Strong software engineering skills in Python Hands-on experience with LLMs and agentic systems, such as tool-using agents, planner-executor patterns, multistep reasoning pipelines, RAG systems Solid understanding of ML fundamentals and practical model usage, including prompting, evaluation, and error analysis Ability to design experiments and interpret results, including ablations, statistical thinking, clear success criteria and measurable KPIs Strong communication and documentation skills including clear write-ups, reproducible experiments, and crisp technical presentations Preferred Qualifications 3+ years experiences in industrial research. Experience with one or more of the following topics: Agent frameworks Structured generation Agent memory management Self-improving agents LLM fine-tuning & reinforcement learning Model optimization for edge Harness engineering Hands-on experience on production of AI systems Additional Information We offer a competitive base salary for this position with a range in US-California of $165,000 - $180,000 along with an annual corporate bonus, and a long-term incentive bonus designed to reward sustained impact and contribution over time. Within the salary range, the individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your well-being matters at Bosch! We offer a a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. Your Recruiter can share more details for this position during the interview process. Learn more about our full benefits offerings by visiting: Equal Opportunity Employer, including disability / veterans.
08/05/2026
Full time
Job Description Job Description Company Description The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. As part of the global research organization, our AI research in Silicon Valley focuses on Foundation Models and Gen AI, Human-AI Collaboration and Trustworthy AI, AI for Advanced Driver-Assistance Systems (ADAS) and Autonomous Systems, AI Systems Engineering, and Industry AI. We develop scalable, intelligent, and trustworthy AI solutions to enable inspiring user experiences for Bosch products and services in application areas such as ADAS, smart manufacturing, enterprise AI, healthcare, smart home, and building solutions. Originating from Bosch AI research in Silicon Valley, our Vision and Language AI Group advances cutting-edge research in two core AI areas: large language models (LLMs) and 3D computer vision. In the LLM space, we focus on AI agents, retrieval-augmented generation, and effective adaptation of LLMs to Bosch domain-specific applications. In 3D vision, we advance spatial intelligence with 3D world models that perceive, reconstruct, and simulate the physical world, enabling reliable embodied control and sim-to-real transfer. By integrating these two areas, we aim to build intelligent systems that can perceive, reason, and communicate seamlessly across both language and spatial environments. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals such as ACL, EMNLP, CVPR, ICCV, ECCV, NeurIPS, AAAI and CoRL. Job Description Responsibilities: Design, build, and evaluate agentic AI systems that can plan, reason, act, and collaborate across tools and environments, including single- and multi-agent setups for complex, long-horizon tasks. Develop robust agent harnesses and evaluation frameworks covering end-to-end testing, regression analysis, trace logging, replayability, and metrics for success, cost, latency, robustness, and safety. Implement self-improving agent loops using reflection, critique, self-debugging, and iterative optimization strategies driven by agent experience, execution traces, and automated feedback. Architect and optimize agent memory systems, including short-term and long-term memory, retrieval-augmented generation, summarization, compression, forgetting policies, and privacy-aware retention. Enable reliable deployment of agents on constrained and edge environments, focusing on model/runtime optimization, partial or offline execution, secure tool-use, and seamless edge-cloud coordination. Qualifications Basic Qualifications Bachelor or master's degree in computer science or engineering Strong software engineering skills in Python Hands-on experience with LLMs and agentic systems, such as tool-using agents, planner-executor patterns, multistep reasoning pipelines, RAG systems Solid understanding of ML fundamentals and practical model usage, including prompting, evaluation, and error analysis Ability to design experiments and interpret results, including ablations, statistical thinking, clear success criteria and measurable KPIs Strong communication and documentation skills including clear write-ups, reproducible experiments, and crisp technical presentations Preferred Qualifications 3+ years experiences in industrial research. Experience with one or more of the following topics: Agent frameworks Structured generation Agent memory management Self-improving agents LLM fine-tuning & reinforcement learning Model optimization for edge Harness engineering Hands-on experience on production of AI systems Additional Information We offer a competitive base salary for this position with a range in US-California of $165,000 - $180,000 along with an annual corporate bonus, and a long-term incentive bonus designed to reward sustained impact and contribution over time. Within the salary range, the individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your well-being matters at Bosch! We offer a a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. Your Recruiter can share more details for this position during the interview process. Learn more about our full benefits offerings by visiting: Equal Opportunity Employer, including disability / veterans.