Renesas Electronics is hiring a Senior Staff Engineer

Renesas Electronics is hiring a Senior Staff Engineer to lead development efforts in AI, MLOps, and signal processing, with a core focus on deploying intelligent systems onto microcontrollers and working directly with customer data. As a leading embedded semiconductor solution provider driven by the purpose To Make Our Lives Easier, we connect over 22,000 professionals globally to build scalable solutions for automotive, industrial, infrastructure, and IoT industries.

What You'll Do

• Architect, develop, and maintain scalable ML product codebases with production-grade quality.
• Lead MLOps strategy including model deployment, monitoring, and lifecycle management.
• Apply advanced signal processing techniques to one-dimensional sensor data (e.g., audio, motor control, accelerometers).
• Collaborate with customers to ingest, debug, and analyze their data for model development and validation.
• Design and implement machine learning models tailored to time-series and sensor data, with a strong grasp of algorithmic foundations (e.g., SVM, decision trees, neural networks, reinforcement learning).
• Optimize and deploy ML models on microcontrollers (MCUs) and embedded platforms.
• Develop smaller, faster models suitable for edge deployment.
• Implement and maintain CI/CD pipelines, GitHub workflows, and automated testing frameworks.
• Write and maintain unit tests, integration tests, and documentation to ensure code quality and reliability.
• Assemble hardware setups (e.g., sensor arrays, embedded boards) and collect data from real-world environments to support model development and validation.
• Mentor junior engineers and contribute to technical leadership across teams.
• Stay current with emerging technologies in AI, embedded ML, and signal processing.

What We're Looking For

• Master's or PhD in Computer Science, Electrical Engineering, or a related field.
• Minimum of 6 years of hands-on experience in software development with a focus on AI/ML and signal processing.
• Proficiency in Python, MATLAB, and at least one other language (e.g., C, C++).
• Deep understanding of ML algorithms, reinforcement learning, and practical experience implementing them from scratch or customizing existing frameworks.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, LIBSVM).
• Strong background in digital signal processing (DSP) for audio and time-series data.
• Hands-on experience with sensor data (e.g., accelerometers, motor control systems).
• Experience working with customer datasets, including debugging and preprocessing.
• Proven ability to optimize model performance and size.
• Extensive experience with CI/CD pipelines, GitHub version control, and automated testing.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong understanding of software engineering best practices and agile development.
• You currently hold a Senior Staff Engineer role in ML/AI development or a Staff Engineer position with at least 1 year of experience in that role.

Nice to Have

• Experience with edge computing or embedded systems.
• Knowledge of real-time systems and latency optimization.
• Contributions to open-source projects or published research in AI/signal processing.

Technical Stack

• Languages: Python, MATLAB, C/C++
• ML Frameworks: TensorFlow, PyTorch, scikit-learn, LIBSVM
• Cloud & Infrastructure: AWS, Azure, GCP, Docker, Kubernetes, GitHub

Benefits & Compensation

• Compensation range: $134,500 - $185,000
• Medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&D, and pet insurance.
• Company-paid life insurance and AD&D, LTD, short term medical benefits.
• Paid sick time, paid holidays, and accrued paid vacation.

Work Mode

This is an onsite position located in Columbia, MD.

Renesas Electronics is an equal opportunity and affirmative action employer, committed to celebrating diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by federal, state or local law.