GenAI Enablement Lead

🏢 Summary: Senior Python Engineer role focused on designing and developing GenAI applications, including architecture, backend services, and AI integrations. The position involves building and maintaining APIs and microservices, integrating GenAI models (e.g., RAG, agentic workflows), and ensuring high-quality, well-tested solutions in cloud environments. The role requires close collaboration across the full project lifecycle while driving technical excellence in AI-powered systems. 🗂️ Requirements: 6+ years of experience in Python development, Fluency in Python ecosystem, Experience with FastAPI or Flask, Experience with SQL and NoSQL databases, Knowledge of clean code and design patterns in Python, Experience writing unit tests, Experience integrating GenAI models into business applications, Knowledge of RAG and agentic workflows, Experience building APIs and microservices, Familiarity with AWS, GCP, or Azure, Familiarity with Continuous Deployment, English C1, Polish C1 📃 Skills: Python, FastAPI, Flask, SQL, NoSQL, GenAI, RAG, APIs, Microservices, AWS, GCP, Azure, CI/CD, UnitTesting 🏢 Description: 🚀 You will be responsible for: Design architecture of GenAI applications, Design, develop, and maintain Python code in AI applications and components, Code review and identification of areas of improvments, Collaborate with data scientists and machine learning engineers to utilize AI models in the applications, Knowledge of basic types of solutions using GenAI models (RAGs, agentic workflows, etc.) Collaborate with other roles (managers, testers, DevOps, etc.) through the whole life cycle of a project, Develop and maintain APIs and microservices for AI integration with other systems, Conduct experiments and evaluations to measure the performance of GenAI models, Stay up-to-date with the latest advancements in GenAI technologies, Contribute to a collaborative and innovative team culture. Additional advantages, but not required directly for the position: Knowledge of another object-oriented programming language (Java/C#/C++) Knowledge of Machine Learning algorithms and libraries (scikit-learn, PyTorch) 👉 What you will need: At least 6 years of experience and fluency in Python development ecosystem, Experience in building back-end services in Python with frameworks like FastAPI (or Flask ), SQL and NoSQL databases , Knowledge of clean code and design patterns in Python , strong attitude to build well structured, high quality solutions, Experience in writing robust unit tests for developed applications, Experience in using GenAI models in building business applications, Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-native technologies, Familiarity with Continuous Deployment lifecycle, Excellent problem-solving and analytical skills, Ability to work independently and as part of a team, Very good knowledge of English (C1) and Polish (C1) Strong communication and documentation skills 👉 What we offer: The opportunity to work on cutting-edge projects in the dynamic field of cloud and data technologies. A supportive and collaborative work environment that fosters professional growth . Competitive remuneration and various bonuses, such as access to private medical care ( Medicover or Luxmed ) and sport ( Multisport ) cards, reimbursement for English classes , access to the Employee Capital Plan ( PPK ) and b udget for professional development. We mostly work remotely , but we ask that you be willing to come to the office occasionally for workshops, client meetings or project-related discussions. Non-work-related activities galore! We have a running team (with a pro coach), internal competitions, from cookery to photography, a ping-pong league, team building, well-being expert seminars. You can suggest beneficiaries for our CF4GOOD charity program . Company culture rooted in respect and cooperation, not competition . You'll be working with great people, open to new challenges and directions. If you are tired of the proverbial corporate treadmill, come to us to rest mentally. If you've had luck with employers, we'll do our best not to buck the trend.

🏢 Summary: Tech Lead AI responsible for designing and scaling GenAI systems based on Python, leading a team in building LLM-powered solutions such as chatbots, AI agents, and RAG systems. The role focuses on architecture, optimization, and integration of AI solutions with scalable backend and cloud environments. It combines hands-on development of advanced AI systems with technical leadership and strategic technology direction. 🗂️ Requirements: Minimum 6 years in software engineering, At least 2 years in Lead/Staff/Principal/Manager role, Expertise in Python, Experience with ML/AI frameworks, Experience building and optimizing LLM systems, Experience with chatbots, AI agents and RAG, Knowledge of scalable APIs and distributed systems, Experience with cloud platforms, Experience with Docker and Kubernetes, Experience with fine-tuning AI models, Knowledge of LangChain and LlamaIndex, Experience with MLOps and CI/CD for AI, Ability to design system architecture and conduct code reviews 📃 Skills: Python, Django, FastAPI, Flask, TensorFlow, PyTorch, HuggingFace, LLM, RAG, LangChain, LlamaIndex, OpenAI, Anthropic, Mistral, LLaMA, AWS, GCP, Azure, Docker, Kubernetes, MLOps, CI/CD, Prompting 🏢 Description: O roli Szukamy Tech Leada AI z silnym doświadczeniem w Pythonie , który będzie odpowiedzialny za architekturę i rozwój systemów opartych na GenAI . Osoba na tym stanowisku pokieruje zespołem inżynierów, wdrażając nowoczesne rozwiązania oparte na LLM, chatbotach, agentach AI i systemach RAG . Twoim zadaniem będzie tworzenie, optymalizacja i skalowanie systemów AI , a także aktywna współpraca z zespołami produktowymi, badawczymi i biznesowymi. Rola wymaga silnego technicznego leadershipu , strategicznego myślenia oraz umiejętności przekładania celów biznesowych na efektywne rozwiązania inżynieryjne . Twoje zadania 🔹 Projektowanie i rozwój systemów GenAI: Tworzenie architektury i infrastruktury AI opartych na Pythonie. Optymalizacja wydajności i skalowalności LLM, chatbotów, agentów AI oraz systemów RAG . Integracja rozwiązań AI z systemami backendowymi i produktami cyfrowymi. 🔹 Zarządzanie zespołem i technologią: Techniczne prowadzenie zespołu programistów, zapewnienie code quality i best practices . Mentoring i rozwój zespołu w zakresie technologii GenAI. Definiowanie roadmapy technologicznej i priorytetów zespołu. 🔹 Innowacje i strategia: Badanie i wdrażanie najnowszych frameworków oraz modeli LLM (np. OpenAI, Anthropic, Mistral, LLaMA). Tworzenie customowych modeli AI oraz optymalizacja procesów inferencji. Eksploracja możliwości fine-tuningu LLM oraz strategii prompt engineeringu . 🔹 Współpraca z biznesem i produktami: Ścisła współpraca z zespołami data science, ML i produktowymi . Konsultowanie architektury i strategii AI z interesariuszami biznesowymi. Tworzenie AI-driven rozwiązań , które realnie wpływają na użytkowników. Czego oczekujemy? Min. 6 lat doświadczenia w inżynierii oprogramowania , w tym 2+ lat jako Lead/ Staff/ Principal lub Manager. Ekspertyza w Pythonie (Django, FastAPI, Flask) oraz frameworkach ML/AI (TensorFlow, PyTorch, Hugging Face). Doświadczenie w tworzeniu i optymalizacji LLM, chatbotów, agentów AI, RAG . Znajomość architektur skalowalnych API i systemów rozproszonych . Doświadczenie w pracy z chmurami (AWS, GCP, Azure) i konteneryzacją (Docker, Kubernetes). Umiejętność prowadzenia code review, architektury rozwiązań i strategii technologicznej . Świetne zdolności komunikacyjne i współpracy z różnymi działami. Doświadczenie w fine-tuningu modeli AI i strategiach retrieval-augmented generation (RAG) . Znajomość technologii LangChain, LlamaIndex, Prompt Engineering . Background w MLOps, CI/CD dla AI .

🏢 Summary: Lead a cross-functional engineering team in building and maintaining cloud-native microservices using Java and modern full-stack technologies. The role combines hands-on software development, technical leadership, cloud architecture, and adoption of Generative AI tools in the development workflow. Candidates will work with AWS services, testing frameworks, and modern front-end and back-end technologies in a scalable enterprise environment. 🗂️ Requirements: 6+ years of Java back-end development experience, Experience leading engineering teams, Node.js expertise, Nest.js expertise, Angular experience, TypeScript proficiency, AWS Lambda knowledge, AWS EC2 knowledge, AWS S3 knowledge, CloudFormation knowledge, EKS knowledge, DynamoDB familiarity, PostgreSQL familiarity, DB2 familiarity, Experience with Splunk, Experience with Honeycomb, Experience with Jest, Experience with Playwright, Experience with Bruno, Hands-on experience with Claude Code, Hands-on experience with GitHub Copilot, Strong analytical and troubleshooting skills, Fluent English communication skills 📃 Skills: Java, Node.js, Nest.js, Angular, TypeScript, AWS, Lambda, EC2, S3, CloudFormation, EKS, DynamoDB, PostgreSQL, DB2, Splunk, Honeycomb, Jest, Playwright, Bruno, Claude, Copilot 🏢 Description: We are looking for a Java Development Team Lead to guide a cross-functional engineering team in designing, building and maintaining cloud-native microservices. The ideal candidate combines strong hands-on Java expertise with leadership skills to drive high-quality, scalable and secure software delivery, while championing the adoption of Generative AI tools such as Claude Code as a core part of the team's daily workflow. Responsibilities Lead the design, development and maintenance of back-end services using Java, Node.js and Nest.js Guide the team in building front-end features using Angular and TypeScript Analyze legacy applications and define target state designs and architectures Drive implementation of cloud-native microservices using AWS services such as Lambda, EC2 and CloudFormation Establish and enforce clean coding practices and standards across the team Champion the use of GenAI tools like Claude Code and GitHub Copilot throughout the software development lifecycle Promote team best practices and guidelines for responsible and effective GenAI usage Oversee unit, integration and non-functional testing using tools like Jest, Playwright and Bruno Facilitate sprint planning, estimation and peer-level code reviews Collaborate with stakeholders including product managers and designers to address technical issues Mentor developers on engineering fundamentals and effective GenAI usage practices Resolve issues proactively to ensure smooth project execution and delivery Requirements 6+ years of experience in Java back-end development, including experience leading engineering teams Skills in Node.js, Nest.js and Angular for full stack development Proficiency in TypeScript Expertise in AWS services such as Lambda, EC2 and S3 Knowledge of CloudFormation and EKS for cloud-native architecture Familiarity with DynamoDB, PostgreSQL and DB2 Background in monitoring tools such as Splunk and Honeycomb Competency in testing tools such as Jest, Playwright and Bruno Showcase of hands-on experience with Generative AI tools such as Claude Code and GitHub Copilot Strong analytical and troubleshooting skills with ability to navigate ambiguity Fluent English communication skills with ability to articulate technical concepts in client-facing roles We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Lead a cross-functional engineering team in developing and maintaining cloud-native microservices using Java and modern full-stack technologies. The role combines hands-on software engineering, technical leadership and adoption of Generative AI tools to improve development workflows and delivery quality. Candidates will work with AWS cloud services, mentor developers and drive scalable, secure software architecture. 🗂️ Requirements: 6+ years of Java back-end development experience, Experience leading engineering teams, Node.js, Nest.js, Angular, TypeScript, AWS, CloudFormation, EKS, DynamoDB, PostgreSQL, DB2, Splunk, Honeycomb, Jest, Playwright, Bruno, Experience with Claude Code, Experience with GitHub Copilot, Strong analytical and troubleshooting skills, Fluent English 📃 Skills: Java, Node.js, Nest.js, Angular, TypeScript, AWS, Lambda, EC2, S3, CloudFormation, EKS, DynamoDB, PostgreSQL, DB2, Splunk, Honeycomb, Jest, Playwright, Bruno, Claude, Copilot 🏢 Description: We are looking for a Java Development Team Lead to guide a cross-functional engineering team in designing, building and maintaining cloud-native microservices. The ideal candidate combines strong hands-on Java expertise with leadership skills to drive high-quality, scalable and secure software delivery, while championing the adoption of Generative AI tools such as Claude Code as a core part of the team's daily workflow. Responsibilities Lead the design, development and maintenance of back-end services using Java, Node.js and Nest.js Guide the team in building front-end features using Angular and TypeScript Analyze legacy applications and define target state designs and architectures Drive implementation of cloud-native microservices using AWS services such as Lambda, EC2 and CloudFormation Establish and enforce clean coding practices and standards across the team Champion the use of GenAI tools like Claude Code and GitHub Copilot throughout the software development lifecycle Promote team best practices and guidelines for responsible and effective GenAI usage Oversee unit, integration and non-functional testing using tools like Jest, Playwright and Bruno Facilitate sprint planning, estimation and peer-level code reviews Collaborate with stakeholders including product managers and designers to address technical issues Mentor developers on engineering fundamentals and effective GenAI usage practices Resolve issues proactively to ensure smooth project execution and delivery Requirements 6+ years of experience in Java back-end development, including experience leading engineering teams Skills in Node.js, Nest.js and Angular for full stack development Proficiency in TypeScript Expertise in AWS services such as Lambda, EC2 and S3 Knowledge of CloudFormation and EKS for cloud-native architecture Familiarity with DynamoDB, PostgreSQL and DB2 Background in monitoring tools such as Splunk and Honeycomb Competency in testing tools such as Jest, Playwright and Bruno Showcase of hands-on experience with Generative AI tools such as Claude Code and GitHub Copilot Strong analytical and troubleshooting skills with ability to navigate ambiguity Fluent English communication skills with ability to articulate technical concepts in client-facing roles We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: The role focuses on analyzing, developing, integrating, and maintaining software solutions that support engineering productivity and agile processes within a large-scale environment. It involves DevOps practices, CI/CD implementation, and system integration of software and hardware. The position requires validating, testing, and documenting solutions to ensure consistency and performance. 🗂️ Requirements: 5+ years of experience in DevOps or related role, Practical understanding of engineering processes, Experience with CI/CD systems (Jenkins, GitHub, GitLab), Basic programming skills in scripting or REST, Ability to perform software and hardware system integration, Experience in software development, validation, and testing 📃 Skills: DevOps, CI/CD, Jenkins, GitHub, GitLab, REST, Scripting, Groovy, Integration, Testing 🏢 Description: The IT Product Enablement Team is supporting Global Software and Hardware Engineering consisting of over 8000 engineers from various disciplines to enhance their productivity and innovation by providing services that enable them to work more efficiently and in an agile work process. In addition to professional support, we focus on developing new solutions to integrate into our tools ecosystemI. The product Enablement team has a critical role in driving extraordinary business results Through a strong partnership with other areas of our business, we bring innovative thinking to every conversation and deliver with integrity. We look for people who bring great ideas and who make our partners’ ideas better. Intellectually curious advisors (not order takers) who focus on outcomes to creatively solve business problems. People who not only embrace change, but who accelerate it. Job Description Analyzes, develops, designs, and maintains software for the organization’s products and systems. Performs system integration of software and hardware to maintain throughput and program consistency. Develops, validates, and tests: structures and user documentation. Basic Requirements 5+ years of experience in a DevOps or related role. Practical understanding of engineering processes Understanding CI/CD systems (Jenkins, GitHub, GitLab, etc) Basic programming skills based on scripting or REST, Groove would be an additional asset Good verbal and written communication skills

🏢 Summary: Senior Staff AI Engineer role focused on developing and deploying Edge AI solutions for in-vehicle health monitoring, anomaly detection, and predictive diagnostics in AI-defined vehicles. The position involves building end-to-end ML pipelines, optimizing models for embedded systems, and leading edge ML architecture in a hybrid Sunnyvale-based environment. Candidates will work with multimodal automotive data, cloud-based LLM integrations, and production-grade AI systems for real-time vehicle reliability. 🗂️ Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field, 10+ years of Machine Learning Engineering experience, 3+ years focused on Edge AI or Embedded Systems, Experience mentoring junior engineers, Expert-level Python, Working knowledge of C++14/17, Proficiency with PyTorch or TensorFlow, Experience with ONNX, TFLite, or TVM, Experience with NLP techniques and sequence modeling, Experience with anomaly detection libraries, Experience deploying ML models to ARM-based edge environments, Ability to lead technical projects from concept to production 📃 Skills: Python, C++, PyTorch, TensorFlow, ONNX, TFLite, TVM, scikit-learn, tslearn, statsmodels, Transformers, LLM, CNN, LSTM, RNN, GRU, Autoencoders, OpenAI, Gemini, Claude, CAN, DBC, UDS, SOME/IP, MQTT, Linux, QNX, TensorRT, SNPE, ADAS 🏢 Description: 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 Sunnyvale, CA, with an expectation to work in the 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. - Integrate 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 determine which data is processed locally versus 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 and working knowledge of modern C++ (C++14/17). - 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 stores, 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 a fast-paced environment. - Experience deploying to Edge environments (e.g., ARM-based), managing memory manually, and working with limited compute resources. - Candidates with a strong Computer Vision / ADAS track record are encouraged to apply. Desired Skills: - MS/PhD in Computer Science, Engineering, or related fields. - Familiarity with automotive formats such as CAN, DBC, UDS, SOME/IP, or MQTT. - Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging. - Experience with NVIDIA TensorRT and Qualcomm SNPE. Benefits & Perks: - 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 and 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 Base Salary Pay Range: $227,000—$300,000 USD

🏢 Summary: Senior Staff AI Engineer role focused on developing and deploying Edge AI models for in-vehicle health monitoring, anomaly detection, and predictive maintenance in AI-defined vehicles. The position involves leading end-to-end ML pipelines, optimizing models for embedded systems, and collaborating on production-grade automotive AI solutions. Hybrid work arrangement based in Sunnyvale, CA. 🗂️ Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field, 10+ years of Machine Learning Engineering experience, 3+ years focused on Edge AI or Embedded Systems, Experience mentoring junior engineers, Expert Python skills, Working knowledge of modern C++14/17, Proficiency with PyTorch or TensorFlow, Experience with ONNX, TFLite, or TVM, Experience with NLP and sequence modeling, Experience with anomaly detection libraries, Experience deploying models to Edge environments, Ability to lead technical projects from concept to production 📃 Skills: Python, C++, PyTorch, TensorFlow, ONNX, TFLite, TVM, scikit-learn, tslearn, statsmodels, NLP, RNN, GRU, LLM, SLM, Transformers, CNN, LSTM, Autoencoders, TensorRT, SNPE, Gemini, OpenAI, Claude, CAN, DBC, UDS, SOME/IP, MQTT, Linux, QNX 🏢 Description: 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 Senior Staff AI Engineer to join the 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 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 environment where your code will directly impact fleet reliability and help build the next generation of the self-aware vehicle. You will collaborate with developers specializing in vehicle software, systems, MLOps, and AI integration for vehicles currently on the road. This is a hybrid role based in Sunnyvale, CA, requiring in-office work 3 days per week. Responsibilities: - Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multimodal data. - Integrate 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 onboard sensors. - Correlate signal anomalies across modalities with system events to identify root causes. - Port and optimize PyTorch/TensorFlow models for CPU/GPU-bound targets or embedded NPUs. - Apply quantization, pruning, distillation, and memory optimization techniques. - Define data strategies for on-device filtering and cloud processing. - Lead architecture for the edge ML pipeline and mentor junior engineers. Requirements: - Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field. - 10+ years in Machine Learning Engineering, including 3+ years focused on Edge AI or Embedded Systems. - Experience mentoring junior engineers. - Expert Python skills and working knowledge of modern C++14/17. - Deep proficiency with PyTorch or TensorFlow. - Experience with inference engines such as ONNX, TFLite, or TVM. - Experience with NLP techniques, sequence modeling, vector stores, or lightweight LLMs/SLMs. - Experience with scikit-learn, tslearn, or statsmodels for anomaly detection. - Ability to lead technical projects in fast-paced environments. - Experience deploying to Edge environments with limited compute resources. Desired Skills: - MS or PhD in Computer Science, Engineering, or related field. - Familiarity with automotive formats such as CAN, DBC, UDS, SOME/IP, or MQTT. - Understanding of Linux/QNX kernel logs and OS-level debugging. - Experience with NVIDIA TensorRT and Qualcomm SNPE. - Strong Computer Vision or ADAS background. Benefits & Perks: - 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 and 14+ paid holidays - Hybrid office work arrangement - Complimentary lunches, snacks, and beverages during on-site working days - Wellness benefit allowance - Phone and Internet reimbursement - Computer Accessory Allowance Base Salary Pay Range: $227,000–$300,000 USD

🏢 Summary: Senior Staff AI Engineer role focused on developing and deploying Edge AI models for in-vehicle health monitoring, anomaly detection, and predictive failure analysis in software-defined vehicles. The position involves leading end-to-end ML pipelines, optimizing models for embedded edge devices, and collaborating on AI systems used in production automotive environments. This hybrid role includes technical leadership, model optimization, and real-time AI deployment for automotive systems. 🗂️ Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field, 10+ years of Machine Learning Engineering experience, 3+ years focused on Edge AI or Embedded Systems, Experience mentoring junior engineers, Expert-level Python skills, Working knowledge of modern C++14/17, Proficiency with PyTorch or TensorFlow, Experience with ONNX, TFLite, or TVM inference engines, Experience with NLP techniques and sequence modeling, Experience with anomaly detection libraries, Ability to lead technical projects from concept to production, Experience deploying models to ARM-based edge environments, Experience managing limited compute and memory resources 📃 Skills: Python, C++, PyTorch, TensorFlow, ONNX, TFLite, TVM, scikit-learn, tslearn, statsmodels, Transformers, LLM, CNN, LSTM, RNN, GRU, Autoencoders, CAN, Ethernet, ARM, NLP, TensorRT, SNPE, MQTT, SOME/IP, DBC, UDS, Linux, QNX, Gemini, OpenAI, Claude 🏢 Description: 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 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 collaborate with developers specializing in vehicle software, systems, MLOps, and AI integration for production vehicle deployments. Expect to experiment with cutting-edge model architectures and advanced development tools. This is a hybrid role based in Sunnyvale, CA, requiring in-office work 3 days per week. Responsibilities: - Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multimodal data - Integrate 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 onboard sensors - Implement logic to correlate signal anomalies across modalities with system events to identify root causes - Port and optimize PyTorch/TensorFlow models into production-grade models for CPU/GPU targets or embedded NPUs - Apply quantization, pruning, distillation, and memory optimization for strict RAM/Flash constraints - Define data strategies for on-device filtering and cloud processing decisions - Lead the architecture for the edge ML pipeline and mentor junior engineers on embedded AI best practices Requirements: - Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field - 10+ years in Machine Learning Engineering with 3+ years focused on Edge AI or Embedded Systems - Proven experience mentoring junior engineers - Expert Python skills and working knowledge of modern C++14/17 - Deep proficiency with PyTorch or TensorFlow - Experience with inference engines such as ONNX, TFLite, or TVM - Experience with NLP techniques, sequence modeling (RNN/GRU), vector stores, or lightweight LLMs/SLMs - Experience with scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data - Ability to lead technical projects from concept to production in fast-paced environments - Experience deploying to ARM-based edge environments with limited compute resources Desired Skills: - MS or PhD in Computer Science, Engineering, or related field - Familiarity with automotive formats such as CAN, DBC, UDS, SOME/IP, or MQTT - Understanding of Linux/QNX kernel logs, process states, and OS-level debugging - Experience with NVIDIA TensorRT and Qualcomm SNPE - Strong Computer Vision or ADAS background Benefits & Perks: - 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 and 14+ paid holidays - Hybrid office work arrangement - Complimentary lunches, snacks, and beverages during on-site workdays - Wellness benefit allowance - Phone and Internet reimbursement - Computer Accessory Allowance Base Salary Pay Range: $227,000—$300,000 USD

🏢 Summary: Staff AI Engineer role focused on developing and deploying Edge AI models for in-vehicle health monitoring, anomaly detection, and predictive maintenance in software-defined vehicles. The position involves building end-to-end ML pipelines, optimizing models for embedded edge devices, and working with multimodal automotive data including logs, traces, Ethernet, and CAN signals. This hybrid Sunnyvale-based role also includes technical leadership and mentoring responsibilities in a fast-paced AI and automotive environment. 🗂️ Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field, 7+ years of Machine Learning Engineering experience, 3+ years focused on Edge AI or Embedded Systems, Experience mentoring junior engineers, Expert-level Python skills, Working knowledge of C++14/17, Proficiency with PyTorch or TensorFlow, Experience with ONNX, TFLite, or TVM inference engines, Experience with NLP techniques and sequence modeling, Experience with anomaly detection libraries for sensor data, Experience deploying models to Edge or ARM-based environments, Ability to lead technical projects from concept to production 📃 Skills: Python, C++, PyTorch, TensorFlow, ONNX, TFLite, TVM, NLP, RNN, GRU, LLM, SLM, scikit-learn, tslearn, statsmodels, ARM, CAN, DBC, UDS, SOME/IP, MQTT, Linux, QNX, TensorRT, SNPE, CNN, LSTM, Transformers, Autoencoders, IsolationForest, Gemini, OpenAI, Claude 🏢 Description: Role Summary: Sonatus is looking for a Staff AI Engineer to 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 vehicle-generated data, including system logs, traces, Ethernet, and CAN signals, to detect and predict subsystem health issues 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 optimization for production environments. The role includes collaboration with vehicle software experts and AI engineers focused on MLOps and AI integration for production vehicles. This is a hybrid role based in Sunnyvale, CA, with an expectation to work in the office 3 days per week. Responsibilities: - Build and train AI Edge models such as Transformers, LLMs, CNNs, LSTMs, and Trees to process application logs, kernel traces, and multimodal data. - Integrate ML workflows, including cloud-based LLM APIs such as Gemini, OpenAI, and Claude, with emphasis on synthetic data creation. - Develop algorithms for clustering log patterns and detecting software regressions, race conditions, and crash precursors. - Design supervised and unsupervised learning models such as Autoencoders and Isolation Forests for monitoring time-series CAN bus and sensor data. - Correlate signal anomalies across modalities with system events to identify root causes. - Port and optimize PyTorch and TensorFlow models for execution on CPU/GPU-bound targets and embedded NPUs. - Apply quantization, pruning, distillation, and memory optimization techniques for constrained edge environments. - Define on-device data filtering and cloud processing strategies. - Lead edge ML pipeline architecture and mentor junior engineers. Requirements: - Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field. - 7+ years in Machine Learning Engineering with 3+ years focused on Edge AI or Embedded Systems. - Experience mentoring junior engineers. - Expert Python skills and working knowledge of modern C++ (C++14/17). - Deep proficiency with PyTorch or TensorFlow. - Experience with inference engines such as ONNX, TFLite, or TVM. - Experience with NLP techniques, sequence modeling (RNN/GRU), vector stores, or lightweight LLMs/SLMs. - Experience with scikit-learn, tslearn, or statsmodels for anomaly detection. - Experience deploying to Edge environments, including ARM-based systems and limited compute resources. - Ability to lead technical projects and communicate trade-offs effectively. Desired Skills: - MS or PhD in Computer Science, Engineering, or related fields. - Familiarity with automotive protocols and formats such as CAN, DBC, UDS, SOME/IP, or MQTT. - Understanding of Linux/QNX kernel logs, process states, and OS-level debugging. - Experience with NVIDIA TensorRT and Qualcomm SNPE. - Strong Computer Vision or ADAS background. Benefits & Perks: - 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 and 14+ paid holidays - Hybrid office work arrangement - Complimentary lunches, snacks, and beverages during on-site workdays - Wellness benefit allowance - Phone and Internet reimbursement - Computer Accessory Allowance Base Salary Pay Range: $197,500—$272,000 USD

🏢 Summary: Staff AI Engineer role focused on developing and deploying Edge AI models for in-vehicle health monitoring, anomaly detection, and predictive diagnostics in AI-defined vehicles. The position involves leading end-to-end ML pipelines, optimizing models for embedded systems, and collaborating on production-grade automotive AI solutions. Hybrid role based in Sunnyvale, CA with opportunities to work on real-time vehicle data, Edge AI, and MLOps integration. 🗂️ Requirements: Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field, 7+ years of Machine Learning Engineering experience, 3+ years focused on Edge AI or Embedded Systems, Experience mentoring junior engineers, Expert-level Python, Working knowledge of C++14/17, Proficiency with PyTorch or TensorFlow, Experience with ONNX, TFLite, or TVM, Experience with NLP and sequence modeling, Experience with scikit-learn, tslearn, or statsmodels, Experience deploying models to Edge or ARM-based environments, Ability to lead technical projects in fast-paced environments 📃 Skills: Python, C++, PyTorch, TensorFlow, ONNX, TFLite, TVM, scikit-learn, tslearn, statsmodels, Transformers, LLM, CNN, LSTM, RNN, GRU, Autoencoders, TensorRT, SNPE, Gemini, OpenAI, Claude, NLP, MLOps, CAN, DBC, UDS, SOME/IP, MQTT, Linux, QNX 🏢 Description: 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 Staff AI Engineer to join our 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 day-to-day operation, including system logs, traces, and vehicle internal signals such as Ethernet and CAN, to detect and predict the health of different subsystems 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 collaborate with developers specializing in vehicle software, systems, MLOps, and AI model integration for production vehicles. The role includes experimentation with advanced model architectures and modern development tools. This is a hybrid role based in Sunnyvale, CA, requiring in-office work 3 days per week. Responsibilities: - Build and train AI Edge models such as Transformers, LLMs, CNNs, LSTMs, and Trees to process unstructured application logs, kernel traces, and multimodal data. - Integrate ML workflows including cloud-based LLM APIs such as Gemini, OpenAI, and Claude, with emphasis on synthetic data creation. - Develop algorithms to cluster log patterns and detect software regressions, race conditions, and crash precursors. - Design supervised and unsupervised learning models such as Autoencoders and Isolation Forests for monitoring time-series data from CAN bus and onboard sensors. - Correlate signal anomalies across modalities with system events to identify root causes. - Port and optimize PyTorch and TensorFlow models for execution on CPU/GPU targets or embedded NPUs. - Apply quantization, pruning, distillation, and memory optimization for constrained edge environments. - Define strategies for on-device filtering and cloud processing. - Lead edge ML pipeline architecture and mentor junior engineers. Requirements: - Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or related field. - 7+ years of Machine Learning Engineering experience with 3+ years focused on Edge AI or Embedded Systems. - Experience mentoring junior engineers. - Expert Python skills and working knowledge of modern C++. - Proficiency with PyTorch or TensorFlow. - Experience with ONNX, TFLite, or TVM. - Experience with NLP techniques, sequence modeling, vector stores, or lightweight LLMs. - Experience with scikit-learn, tslearn, or statsmodels. - Ability to lead projects in fast-paced environments and communicate technical trade-offs. - Experience deploying to ARM-based Edge environments with constrained compute resources. Desired Skills: - MS or PhD in Computer Science, Engineering, or related field. - Familiarity with automotive protocols and formats such as CAN, DBC, UDS, SOME/IP, or MQTT. - Understanding of Linux/QNX kernel logs, process states, and OS-level debugging. - Experience with NVIDIA TensorRT and Qualcomm SNPE. Benefits & Perks: - Health care plan including Medical, Dental, and Vision. - Flexible and Dependent Care Expense program. - 401(k) retirement plan. - Life insurance. - Unlimited paid time off and paid holidays. - Hybrid office work arrangement. - Complimentary lunches, snacks, and beverages on-site. - Wellness allowance. - Phone and Internet reimbursement. - Computer accessory allowance. Base Salary Pay Range: $197,500 — $272,000 USD