Senior Staff Engineer

Renesas Electronics • Columbia, MD

1d • $134,500 - $185,000 • Onsite

About The Position

We are seeking a highly skilled and hands-on Senior Staff Enginee r to lead development efforts in AI, MLOps, and signal processing, with a strong emphasis on deploying intelligent systems on microcontrollers and working directly with customer data. This role demands not only proficiency in machine learning frameworks but also a deep understanding of the underlying algorithms and their practical application to real-world sensor data. The ideal candidate will also bring extensive experience in software production development, including CI/CD pipelines, GitHub workflows, and rigorous testing practices.

Requirements

• Master's or PhD in Computer Science, Electrical Engineering, or related field.
• Minimum 6 years of hands-on experience in ML/AI development.
• Candidates should 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.
• 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 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.

Nice To Haves

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

Responsibilities

• 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 platofrms. 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.

Benefits

• Renesas offers a full range of elective benefits including 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.
• In addition to elective benefit options, benefited employees receive company-paid life insurance and AD&D, LTD, short term medical benefits as well as paid sick time, paid holidays, and accrued paid vacation.
• New employees will attend a detailed benefit orientation to learn more about our many benefits and resources

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees