22 jobs found

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

Job Description Job Description Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that's why we're building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver , our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our robotics team is growing and we are looking for a Software Engineer to join our Sensor Data and Calibration team. We are searching for an engineer with robotics and machine learning expertise to develop synthetic sensor simulation models and algorithms. The ideal candidate has hands-on experience in the research, development, and implementation of machine learning methods (e.g., NeRF or Gaussian splatting) for generating synthetic sensor data (photorealistic images, realistic lidar and/or radar, etc.). About the Work Research, develop, and implement state-of-the-art synthetic sensor simulation methods Analyze and characterize the realism and utility of synthetic sensor data Answer critical questions about sensor data and autonomy performance Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements Role is scoped as a Senior/Staff IC with the flexibility to grow into a Tech Lead/TLM. About You One of PhD in machine learning, computer science, electrical engineering, robotics, or related field, and 3+ years of industry experience Masters and 4+ years of industry experience 5+ years of industry experience Deep understanding of ML fundamentals with hands-on experience in training and evaluating modern ML models Strong Python skills with experience in deep learning frameworks, e.g., PyTorch, TensorFlow, or Jax Bonus Points Deep understanding of 3D geometry and state estimation fundamentals Proficiency in systems coding Experience in simulating/modeling real sensors (camera, lidar, radar, IMU, etc), including noise modeling Experience in modern ML graphics techniques, e.g., NeRF, Gaussian Splatting, and/or generative models. Experience in building ML pipelines and optimizing/productizing ML models Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA) At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $291,150 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.

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 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 Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more. Powered by JazzHR ZnRHQBiPpf

Job Description Job Description Looking for a Senior Forward Deployed AI Engineer to lead the deployment and customization of AI-powered solutions for real-world customer environments. This role sits at the intersection of engineering, product, and customer success - working directly with users to understand complex workflows and translate them into practical, high-impact AI solutions. You'll operate in a fast-paced, high-ownership environment, rapidly prototyping, iterating, and deploying systems that deliver immediate value. This role requires strong technical depth, a problem-solving mindset, and the ability to navigate ambiguity while staying focused on outcomes. What you'll do: Partner closely with customers to understand workflows and identify opportunities to apply AI/ML solutions Design, customize, and deploy AI-driven systems tailored to specific customer needs Rapidly prototype and iterate on solutions based on real-time feedback Break down complex problems into actionable steps and deliver results in ambiguous environments Integrate a wide range of AI/ML technologies to solve diverse, real-world challenges Provide hands-on technical support to ensure successful implementation and adoption Collaborate with internal engineering teams to inform product development and improvements Stay current with advancements in AI/ML and apply them to practical use cases Mentor other engineers and contribute to a strong, collaborative engineering culture Influence product direction by bringing insights from customer engagements and emerging technologies What we're looking for: 4+ years of experience in software engineering, data engineering, or machine learning Strong coding ability with a focus on building and shipping real-world systems Experience with or strong interest in Large Language Models (LLMs) and prompt engineering Ability to quickly learn new technologies and adapt in fast-changing environments Strong bias toward delivering business value over purely theoretical work Comfort operating across a wide range of technical problems rather than specializing narrowly Proven ability to break down complex systems and execute effectively High resilience, resourcefulness, and ownership mindset Strong communication skills and ability to work directly with customers Interest in applying technology to real-world domains and making meaningful impact Nice to have: Experience or interest in healthcare or regulated environments Proficiency in Python Experience with machine learning and neural networks

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: We are seeking a Senior Staff AI Engineer with a combination of architectural expertise and production rigor to lead the development of an Agentic Framework to support our AI applications. In this role, you will be the technical anchor for our AI offerings, working to deliver a production-grade Agentic Operating Layer for software-defined vehicles. This is a 50% Architecture / 50% Implementation position. You will be responsible for designing and implementing an extensible architecture that bridges high-velocity vehicle telemetry with sophisticated AI reasoning. We need a leader who is collaborative by nature but decisive in execution-someone who can drive architectural consensus and take full accountability for the performance, safety, and scalability of the resulting system. Responsibilities: Lead the architecture and design of an extensible AI platform. Drive architectural consensus across teams on AI-core decisions to ensure platform unification. Lead the development of agentic orchestration by designing and implementing mission-critical components that allow AI agents to decompose complex goals into actionable sub-tasks. Design and implement a versioned prompt registry allowing for model-agnostic routing and A/B testing of system prompts Engineer the privacy shield for PII redaction and the hallucination verifier to audit AI-generated actions before execution Conduct the full cycle of data modeling and algorithm development, including modeling, training, tuning, validating, deploying, and maintaining services (AI breadth). Strong domain expertise in the AI area, including LLM, RAG, fine-tune large models, traditional ML models, etc. (AI depth) Stay current with industry trends and advancements in data science and AI technologies. (State-of-the-Art) Perform data analysis and offer insights to inform business decisions across multiple domains. Adhere to data privacy and security protocols to uphold the confidentiality of sensitive information. Document and communicate technical designs, processes, and best practices to stakeholders using visualizations and presentations. Take charge of projects, ensuring timely completion in a dynamic work environment. Qualifications: Master's or PhD in Computer Science, Engineering, Mathematics, Applied Sciences, or a related field preferred. Bachelor's degree required. 10+ years of software engineering experience with 4+ years dedicated to shipping production-scale AI/Agentic systems. You have a track record of moving projects from whiteboards to global cloud deployments. Strong programming skills in languages such as Python, Java, or C++, with hands-on experience in relevant frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Expert-level experience with stateful orchestration frameworks (e.g., LangGraph, AutoGen, or similar). You understand the nuances of managing state across complex, multi-step AI missions. Strong experience grounding AI in structured/unstructured Big Data environments. Practical knowledge of traditional databases, streaming analytics, and Vector databases. Proven experience building multi-agent systems and frameworks with adaptive orchestration Deep understanding of Jailbreak Detection (e.g., LlamaGuard) and PII masking techniques to ensure safe LLM interactions in regulated environments In-depth knowledge and understanding of current machine learning algorithms, AI technologies, and platforms. Solid experience in data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Strong knowledge of software development best practices, version control systems, and agile methodologies. Results-driven with a positive can-do attitude and excellent problem-solving skills. Exceptional verbal and written communication skills, with the ability to collaborate effectively with cross-functional teams. Experience in the automotive industry is highly desirable. Experience building multi-tenant "Platform-as-a-Service" (PaaS) models is desirable. Benefits Offered: Competitive compensation and equity program 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, 15 paid holidays Hybrid office work arrangement/flexibility Perk Offerings include: Complimentary lunches, snacks, and beverages during on-site working days Wellness benefit allowances (towards gym membership and fitness programs) Internet reimbursement Computer Accessory Allowance Employee Engagement Offerings: Departmental team building and outings Employee Referral Program Culture/Employee Satisfaction Surveys - Feedback matters! 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 $227,500-$300,000 USD

Job Description Job Description RETHINK MANUFACTURING The only way to ignite change is to build the best team. At Bright Machines , we're innovators and experts in our craft who have joined together to manufacture the AI and data center infrastructure at the edge. We believe unifying software, intelligent automation, and data is the answer to delivering quality and flexibility at scale. We deliver products to meet the demands of today while continuously investing in our Bright Factory model to take advantage of what comes next. Working with us means you'll have the opportunity to make lasting, impactful changes for our company and our customers. If you're ready to apply your exceptional skills to a brighter way of manufacturing AI infrastructure, we'd love to speak with you. ABOUT THE ROLE As a senior Robot Perception Engineer on the Smart Robotics team at Bright Machines, you will be a hands-on senior contributor responsible for productizing visual inspection solutions for our automation platform. You will own the full pipeline-from algorithm development to production deployment-turning prototype inspection capabilities into reliable, high-throughput features that operate at scale across our automation lines. In this role, you will develop and optimize computer vision and deep learning models for defect detection, classification, and visual validation. You will collaborate closely with cross-functional teams, including Mechanical Engineering and Manufacturing Operations, to design end-to-end inspection solutions that deliver consistent, accurate results under real-world factory conditions. Additionally, you will have the opportunity to shape the inspection product roadmap and drive the adoption of cutting-edge machine learning techniques in an industrial setting. WHAT YOU WILL BE DOING Develop and optimize visual inspection algorithms for defect detection, anomaly detection, classification, and quality validation using deep learning Optimize model inference for GPU deployment, leveraging CUDA, TensorRT, and related acceleration frameworks Collaborate with Mechanical engineers to design illumination setups that maximize inspection accuracy and robustness Build and maintain data pipelines for model training, evaluation, and continuous improvement Partner with platform team to establish MLOps practices for model versioning, experiment tracking, automated retraining, and production model monitoring Harden inspection solutions for production reliability, including monitoring, alerting, and graceful degradation Work with service engineering and field teams to deploy inspection solutions and support customer rollouts Define metrics and benchmarks to measure inspection accuracy, throughput, and reliability WHAT YOU WILL BRING MS or PhD in Computer Science, Electrical Engineering, or a related field, or the equivalent in experience with evidence of exceptional ability. 5+ years of relevant experience in computer vision and/or machine learning Strong programming skills in Python Deep experience with PyTorch for model development and training Experience optimizing ML models for GPU inference in production environments Track record of shipping ML/CV models from prototype to production Experience with image acquisition, camera systems, and sensor integration IT WOULD BE GREAT IF YOU HAD Knowledge of lighting and optics for machine vision (diffuse/directional illumination, lens and filters) Experience with industrial camera systems and standards (GigE Vision, GenICam, CoaXPress) C/C++ experience for performance-critical components Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) Experience with data annotation, labeling workflows, and active learning strategies Experience with ROS2 Understanding of manufacturing processes and quality control methodologies Publications or patents in computer vision, deep learning, or related fields BE EMPOWERED TO CHANGE AN INDUSTRY Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure production. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers, neoclouds, and leading Original Equipment Manufacturers (OEMs) to reduce their time to revenue. With its Bright Factory model, Bright Machines builds higher quality data center infrastructure at scale, addresses increasing market demands for computing power due to the surge of AI, and answers the call to the U.S. national mandate to reshore manufacturing. Bright Machines is headquartered in San Francisco, California, with an integration center in Guadalajara, Mexico. The company has been recognized as one of Forbes' AI 50, awarded "Best AI-based Solution for Manufacturing" by AI Breakthrough, named a "Technology Pioneer" by the World Economic Forum, and highlighted by several other leading technology and innovation organizations.

Job Description Job Description Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. You will be part of an organization with strong leadership and a transparent, respectful culture that enables you to reach your full potential. In this role, you will: Develop, coordinate, and execute verification and validation test plans for Pose monitors using Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) environments. Analyze and triage pipeline results that contribute to key launch-blocking metrics for software and system releases. Collaborate with cross-functional teams, including software developers, hardware engineers, systems engineers, simulation developers, and safety experts, to identify and mitigate risks. Track and report test campaign results to demonstrate feature readiness during safety clearance for each Zoox milestone. Develop metrics and performance benchmarks for V&V campaigns, driving continuous improvement of test coverage and efficiency. Contribute to the development of risk analysis models to quantify behavioral risk when testing gaps exist. Qualifications MS or higher degree in a technical field, such as Mechatronics, Mechanical, Electrical, Aerospace, or Systems Engineering. 5+ years of hands-on systems integration and validation experience (simulation testing, SIL/HIL testing, structured testing, and end-to-end product validation) with a focus on delivering complex systems to production. Proficiency in Python for data analysis, test scripting, and automation. Experience with requirements and test traceability tools such as Polarion, Jama, DOORS, or TestRails. Strong systems-level thinking and the ability to understand and navigate complex technical systems. Basic proficiency with probability and statistics. Ability to grapple with ambiguity and collaborate with cross-functional teams. Bonus Qualifications Experience with autonomous vehicles, robotics, or other safety-critical systems. Experience with simulation environments and hardware-in-the-loop (HIL) testing for pose estimation or perception systems. Experience with fault protection system design and validation. Familiarity with industry safety standards such as ISO 26262, ISO 21448 (SOTIF), ARP 4754, or ARP 4761. Experience with Linux systems and containerized testing environments. Proficiency with SQL for test data analysis. Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to or your assigned recruiter. A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills. 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 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 Who We Are & Why Join Us Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries energy, mining, manufacturing, aerospace, defense, and logistics accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale. Cutting-Edge AI Innovation Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact Work on AI-driven projects that drive real change across industries and improve lives. Learn more at: About the Role As a Senior AI Engineer at Avathon, you will play a key role in designing and delivering advanced AI solutions with a strong emphasis on Generative AI and Large Language Models (LLMs). You will apply scientific rigor to develop scalable, production-ready machine learning systems that drive measurable business impact, working on challenging problems in forecasting, demand planning, renewable energy optimization, anomaly detection, and prescriptive maintenance. With minimum 5 years of industry experience, you are expected to bring strong expertise in statistical modeling, ML engineering, and modern AI architectures, particularly in GenAI and LLM-based applications. This role offers the opportunity to work on high-impact projects that shape next-generation AI capabilities within the organization. You Will Design, develop, and deploy machine learning and Generative AI solutions to solve complex business problems Build, fine-tune, and optimize Large Language Models (LLMs) and transformer-based architectures for real-world applications Apply rigorous scientific methodologies to experimentation, model evaluation, and performance optimization Develop scalable ML pipelines and production-grade systems in collaboration with Engineering teams Conduct prompt engineering, model alignment, evaluation, and performance benchmarking for GenAI applications Work closely with Product, Engineering, and Business stakeholders to translate ambiguous requirements into data-driven AI solutions Instrument and monitor LLM applications in production using observability tools, tracking cost, latency, quality, and drift Contribute to model governance, responsible AI practices, and performance monitoring in production environments Stay current with advancements in Generative AI, LLM research, and applied machine learning, incorporating relevant innovations into company solutions You'll Have Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field Minimum 5 years of hands-on industry experience in AI engineering, machine learning, data science, or applied AI roles Strong experience with Generative AI frameworks and Large Language Models (e.g., transformer architectures, fine-tuning, RAG systems) Proficiency in Python and modern ML/AI libraries such as PyTorch, TensorFlow, Hugging Face, or equivalent ecosystems Solid understanding of statistical modeling, experimentation, and model evaluation methodologies Experience building and deploying ML models into production environments Familiarity with data engineering workflows and cloud-based ML platforms (AWS, GCP, or Azure) Strong problem-solving skills with the ability to work independently on complex and ambiguous problem statements Excellent communication skills with the ability to present technical insights clearly to cross-functional stakeholders Preferred Qualifications Experience implementing Retrieval-Augmented Generation (RAG), vector databases, and embedding-based search systems Hands-on experience with LLM observability platforms (e.g., Langfuse, LangSmith, Arize Phoenix, Weights & Biases) for tracing, cost tracking, and quality monitoring in production Experience with LLM evaluation frameworks (e.g., RAGAS, DeepEval) and evaluation patterns such as LLM-as-judge and automated regression testing Practical experience deploying LLM applications with guardrails, prompt versioning, hallucination detection, and model drift monitoring Exposure to distributed training, model optimization, and scalable inference architectures Knowledge of MLOps practices, CI/CD for ML (Travis CI, Jenkins), and model lifecycle management Prior experience applying AI solutions in industrial or asset-intensive environments Experience working in fast-paced startup or product-driven environments Industry experience in one or more of the following domains: Mining, Oil & Gas, Aerospace, Supply Chain, Logistics, or Renewable Energy Benefits & Perks What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees we'd love to connect and share more! Evolving culture with the opportunity to drive new ideas and technology Stock Option Grants Medical Coverage and Parental Leave Plans 401k with Employer Match Monthly Technology Allowance Newly renovated office space located near Pleasanton, CA including fully stocked beverage and snack areas Contract and temporary roles are not eligible for the above benefits. Compensation Pay Range: $130k - $155k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week. Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.

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 We are a well-funded startup on a mission to build the nervous system for AI-powered robots in industrial applications. Founded by leading robotics researchers, we are growing our dynamic, world-class team to deploy robots at scale. Join us in helping people handle more throughout the supply chain! We are seeking a Senior Robotics Research Engineer to design and develop fundamental new contributions to core robotics libraries and runtime application software for Ambi products, focused on new technology for the future. You will work closely with the Software team and the CTO. In this role you will: Independently develop robot applications and capabilities (controls, planning, perception) Lead R&D projects for new AI-driven robot skills, powered by foundation models Contribute to AmbiOS core libraries in areas such as: (a) scalable AI training, algorithms, models, and evaluation, (b) perception modules, (c) image and point cloud processing, (d) motion planning policies, (e) collision checkers Support software deployments to AI-powered robotic systems in production with global brands Modify existing software and configurations for new customers You are a good fit if you have: Eagerness to learn, solve challenging problems, and lead with curiosity A desire for career growth, ownership of your work, and making an impact Excitement about amplifying human potential with state-of-the-art robotics Proficiency in C++, Python, Linux, Git, and, Docker Expertise in motion planning, contact physics, machine learning, and computer vision Experience in the following areas: robotics (3D rigid geometry, kinematics, motion planning), software architecture, state machines, multi-processing, operating systems (must know UNIX), drivers (cameras, sensors, other equipment), and software update systems An MS with four years of experience in commercial robotics software development or equivalent or PhD in a very related subject (BONUS) Experience in Rust In addition to competitive compensation, we offer benefits such as: Health, dental, and vision insurance 401k with 5% matching by Ambi Equity ownership Unlimited PTO Partial WFH Free parking on site at HQ Access to a full gym at HQ Free lunches 2x per week PLEASE NOTE: All applications must be submitted online for equitable review. We do not accept or review submissions sent via email, including to individual team members or engineers. This policy ensures a fair and streamlined process for everyone. FOR RECRUITERS: This position is direct-hire only; unsolicited resumes from recruiters will not be considered and may result in a fee waiver. 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 About Tahoe Therapeutics Tahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world's largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response. By combining cutting-edge machine learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them. Your role With Tahoe-100M, we solved one of the fundamental bottlenecks in building a virtual model of the cell: generating massive, perturbation-rich, single-cell datasets that capture real biological causality. With Tahoe-x1, we removed the second bottleneck: creating a modern platform for rapid iteration on model architectures and designs in a cost-efficient manner and at scale. At Tahoe, we embody a simple philosophy: build in the open, shoot for the moon, and we're looking for people who want to push the frontier of what's possible. As a Senior Machine Learning Engineer, you will play a leading role in designing the next generation of foundation models of gene regulatory networks powered by Tahoe's large scale single-cell datasets such as Tahoe-100M and beyond. This role is well-suited for someone with a strong background in machine learning and statistics, and an interest in applying cutting-edge breakthroughs in ML to meaningful problems in drug discovery. We are looking for non-incremental thinkers with the skills to help build models that can make a real impact on drug discovery. Qualifications - Required Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience. Exceptional engineering skills to iterate quickly on data processing and training pipelines Experience in building, testing, training, and deploying modern neural network architectures such as Transformers. Experience with frameworks like PyTorch, Tensorflow, Keras, JAX and the ability to write hardware optimized code for distributed training Qualifications - Desirable Experience with distributed deep learning using frameworks such as HF Accelerate, Deepspeed, Composer, TorchTitan, Megatron etc. Experience with training large neural networks on multiple compute nodes. Key Responsibilities Stay at the forefront of ML and computational biology research and rapidly adopt state-of-the-art techniques to train AI virtual cell models on our massive single cell datasets. Work together with ML Scientists to develop the next generation of compute optimized models like Tahoe-x1. Benefits Unlimited Paid Time Off (PTO). Monthly Lunch budget One-time Office set up budget US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents. This position requires on-site presence at our South San Francisco office a minimum of three days per week. We welcome applicants who require visa sponsorship and provide work authorization support for qualified candidates. 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 The Perception team at Zoox creates the "eyes and ears" of our self-driving robots. Navigating safely and efficiently in complex environments requires detecting, classifying, tracking, and understanding various attributes of surrounding objects-all in real-time and with exceptional accuracy. As an engineer in the Scene Understanding team, you will develop advanced Vision-Language-Action (VLA) models that perceive our vehicle's surroundings to identify hazards and make driving suggestions. You will utilize VLA models for detecting rare events and ensuring safe driving in these situations. You'll work with state-of-the-art machine learning models that operate in real-time on our robotaxi platform with minimal latency. Collaborating with world-class engineers and researchers across sensors, planning, and other teams, you'll have access to premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions. In this role, you will Design and train Vision-Language-Action (VLA) solutions for robotaxis Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel Lead the full post-training stack for VLMs and VLAs, including C ontinual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following. Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior Partner with cross-functional teams to integrate perception signals Qualifications MS or PhD in Computer Science or related field Background in deep learning solutions for VLM and VLA models Track record in post-training large-scale models, CPT, SFT, RL Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM) Bonus Qualifications Deep knowledge of cutting-edge computer vision techniques Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA) Experience with integrating large language models to various tasks. Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About Zoox Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to or your assigned recruiter. A Final Note: You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills. 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 The Perception team at Zoox is fundamental to our autonomous vehicle technology, creating the understanding of the world for our self-driving robots. We enable safe and efficient navigation in complex environments through sophisticated detection, classification, and tracking systems. As a software engineer on the perception mapping team, you will be a key contributor to Zoox's online mapping initiative. You will design, train, validate, and integrate into the stack ML models that detect semantic map elements in the world. Your work will touch on all aspects of ML development, including data gathering, labeling, training, validation, and onboard integration. Your work will enable important milestones to scaling and autonomy capabilities and will be critical to the success of Zoox. In this role, you will: Curate, validate, and label datasets for model training and validation Research, implement, and train ML models to perform semantic map element detection Closely collaborate with validation teams to formulate and execute model validation pipelines Integrate models into the greater onboard autonomy system within compute budgets Be a technical leader on the team, maintaining coding and ML development best practices and contributing to architectural decisions Qualifications: MS or PhD or equivalent experience (5+ years) in Computer Science or related field Experience in computer vision or robotics Experience with training and deploying deep learning models Experience with with Python libraries (pytorch, numpy) Bonus Qualifications: Experience with C++ Experience with CUDA and/or GPU programming Experience with mapping related ML techniques Base Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. 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 Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity. Since 2017, we've been on a mission to use AI to resolve as many conversations as possible while elevating human agents to do what they are uniquely good at. We are looking for a Senior Machine Learning Engineer with 5+ years of experience to join our small but mighty ML team building production-grade AI voice agents used by enterprise customers like AAA and Fanatics. You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ship LLM-powered systems that handle real, high-stakes conversations at scale - not just run experiments. What will you be doing? Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences Help set the team's strategic direction, cultivating an environment that encourages innovation and professional growth Actively engaging in all aspects of development, from ideation and experimentation to implementation and deployment Collaborating with various teams and product managers to develop and implement ML based solutions, ensuring performance optimization and alignment with broader business goals Requirements: 5 - 10 years of experience in applied ML engineering, building production systems in Python with LLMs or NLP (Mandatory) Experience building production systems in Python (Mandatory) Familiarity with low-latency production ML systems (Mandatory) Experience working at a high-growth startup (Mandatory) Background in NLU, NLP, or conversational AI (Nice-to-have) BS/MS/PhD in CS, ML, Mathematics, or closely related field with ML coursework (Mandatory) Why you should join Industry leader in Voice AI for customer service since 2017 - powering enterprise customers like AAA and Fanatics where 50%+ of callers get fully resolved by the bot with higher satisfaction scores than human agents. $113M raised from top-tier investors including Stripes, Salesforce Ventures and Norwest - Series B closed in 2022 at $78M with strong backing from day one. Work on genuinely cutting-edge AI problems - low latency inference, hallucination reduction, prompt injection guardrails and dynamic conversation design at the frontier of what's possible with LLMs today. Small team means real ownership and real impact - every improvement you ship moves the needle for enterprise customers in high-stakes scenarios (think: someone stranded on the road calling AAA). Remote-first with strong perks - flexible vacation, paid sabbatical after 5 years, comprehensive health benefits, wellness stipend and a tech/learning stipend for conferences, books and courses. Competitive salary ($180K-$230K) plus meaningful equity.

Job Description Job Description About the Role A growing AI and Data Science team at a healthcare-focused company is looking for a Senior Machine Learning Engineer to take ownership of complex, enterprise-scale ML initiatives. This is a W2 contract role for work-authorized candidates (no visa sponsorship available). You'll work in a fast-paced environment building production-grade ML solutions that directly impact patient outcomes and healthcare operations - with a strong emphasis on compliance, reliability, and end-to-end ownership. Ideal candidates bring 8+ years of professional ML engineering experience and a mandatory background in the healthcare industry , including hands-on experience with HIPAA-compliant systems and sensitive patient data. What You'll Do Own the full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, monitoring, retraining, and maintenance. Design and build scalable, production-ready ML systems with high availability, performance, and reliability. Develop and maintain MLOps pipelines - including CI/CD, model registry, feature stores, automated deployment, monitoring, and rollback strategies. Monitor production models for drift (model, data, accuracy degradation) and overall system health. Build and integrate REST APIs to connect ML services into enterprise cloud applications. Optimize models for latency, scalability, reliability, and operational cost. Provide technical leadership on AI/ML initiatives across the organization. Collaborate with Data Engineers, Software Engineers, Product Managers, Clinical teams, and business stakeholders. Ensure strict compliance with HIPAA, PHI, PII, and enterprise security standards throughout all ML workflows. What We're Looking For Required - Dealbreakers: 8+ years of professional software engineering and machine learning experience. Healthcare domain experience is mandatory - including HIPAA compliance and handling of sensitive patient data (PHI/PII). Demonstrated ownership of end-to-end ML lifecycle from data preparation through deployment, monitoring, and retraining. Experience designing and operating production-grade ML systems at scale. Hands-on MLOps: CI/CD pipelines, model registry, feature stores, automated deployment, monitoring, and rollback. Required Technical Skills: Languages: Python, SQL Platforms: Databricks (production), Apache Spark (distributed computing), MLflow, Feature Store, Model Registry Cloud: Azure, AWS, and/or GCP for ML workloads Infrastructure: Docker, Kubernetes, REST APIs, Git, CI/CD pipelines Strong debugging and performance-tuning skills; excellent stakeholder communication. Nice to Have: LLMs in production, prompt engineering, RAG, and/or GenAI applications Scala Azure ML, SageMaker, or Vertex AI Distributed ML architecture design HIPAA-compliant AI solution design experience Compensation & Details Rate: $70-75/hr on W2 (equivalent to $145,600-$156,000 annualized) Type: W2 Contract Visa sponsorship: Not available - open to all work-authorized candidates Location Primary location: San Francisco, CA . Additional locations considered include Los Angeles, CA and New York City, NY. Remote-friendly role.

Job Description Job Description Description: On-site in Jersey City, NJ Our client seeks a senior software engineer to lead design and development of next-generation electronic trading systems and data infrastructure. The role requires hands-on leadership building scalable, resilient, and high-performance platforms for capital markets, with emphasis on KDB+/q, Python, and AI/ML applied to time-series data. You will collaborate across quant, product, and engineering teams, mentor peers, and deliver robust production systems that support research, backtesting, and real-time trading workflows. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $80.00 to $90.00/hr. w2 JN -08 Responsibilities: Lead design and development of low-latency, high-throughput trading systems and workflows. Design, develop, and optimize KDB+/q databases and analytics for high-volume market data. Develop Python-based AI and quantitative models for research, prediction, classification, and signal generation. Apply machine learning techniques to time-series data including feature engineering, model training, and evaluation. Build research and backtesting frameworks integrating AI models with historical data. Translate quantitative and ML research into production-ready, resilient systems. Integrate AI models into real-time and batch pipelines. Optimize analytics and model evaluation for performance, stability, and scalability. Collaborate with quants, product owners, and engineering on deployment and monitoring. Support production systems and participate in on-call rotations, including occasional weekend support. Experience Requirements: 10+ years of professional experience in quantitative finance or trading systems. Advanced proficiency with KDB+/q for time-series modeling, high-performance querying, and real-time and historical analytics. Strong Python for quantitative analysis, AI/ML model development, and integration with KDB+ and downstream systems. Experience with large-scale, high-frequency, or noisy datasets. Solid software engineering practices including Git, testing, and modular design. Experience with AI developer assist tools such as GitHub Copilot. Experience with CI/CD tools such as GitHub, Maven, Jenkins, Artifactory, and uDeploy. Hands-on experience with AWS or other cloud platforms. Familiarity with Java or other object-oriented languages. Experience with Linux, shell scripting, and production support. Clear communication with quants, traders, and engineers. Education Requirements: Bachelor's degree in Mathematics, Computer Science, Engineering, Information Technology, or equivalent. Recruitment Transparency Notice Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening and hiring process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team ( , ) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group's use of these tools, including AI tools, as part of the application and hiring process. Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.If anyone reaches out to you about an open position connected with Eliassen Group, please ensure that you are working directly with us by confirming the following: When you work with Eliassen Group, all email communication will come from an address, never Gmail, Yahoo, etc. Eliassen Group will never ask you for personal information (home address, bank account, or check routing number) until you have worked with someone clearly associated with Eliassen Group. If you have any indication of fraudulent activity, please contact . About Eliassen Group: Eliassen Group is a strategic consulting firm that helps organizations reach further and achieve more through our technology, business advisory, and life sciences solutions. For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent capabilities to expand our clients' capacity and accelerate meaningful outcomes. We are driven by a purpose to positively impact the lives of our employees, clients, consultants, and the communities we serve. Eliassen is committed to building a diverse and inclusive team from a variety of backgrounds, perspectives, and skills. We are an Equal Opportunity and Affirmative Action Employer and all employment decisions are based on merit, performance, and business needs. Eliassen does not discriminate on the basis of race, color, gender identity or expression, sexual preference or orientation, sex (including pregnancy, childbirth, and related medical conditions), marital status, creed, religion, physical or mental disability, genetic information, military or veteran status, age, ancestry, national origin, citizenship status, prohibited criminal record inquiries of applicants and employees, or any other category protected by federal, state, or local laws. Don't miss out on our referral program! If we hire a candidate that you refer us to then you can be eligible for a $1,000 referral check!