Machine Learning Engineer

What You'll Do

• Partner with Data Scientists to transform research algorithms into robust, production-quality software.
• Implement machine learning algorithms in high-performance C++ and Python with a focus on maintainability, scalability, and real-time performance.
• Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development.
• Design and implement AI agents, agentic workflows, and LLM-powered applications.
• Deploy and maintain AI workloads across edge, near-edge, and cloud environments.
• Collaborate across engineering and research teams to transition prototypes into production systems.

What We're Looking For

• This position requires working directly or indirectly with the US Government in restricted environments.
• Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.
• This is NOT a fully remote position!
• Required: BS, MS, or PhD in Computer Science, Electrical Engineering, Applied Mathematics, Machine Learning, AI, Robotics, or a related field.
• Strong hands-on programming experience in C++ and Python.
• 3-5 years of experience developing and deploying machine learning systems in production environments.
• Experience building AI agents, LLM-based applications, or intelligent automation systems.
• Strong problem-solving skills and ability to work across the full development lifecycle.
• Excellent written and verbal communication and collaboration skills.

Someone Who Will Thrive In This Role

• Enjoys solving difficult technical challenges that span algorithms, software, and deployment.
• Enjoys bridging the gap between research and production, finding practical engineering solutions that make advanced ML usable in real-world products.
• Takes ownership and drives projects from concept through production.
• Continuously explores new AI, ML, and agentic technologies.
• Works effectively across multidisciplinary teams.
• Balances research innovation with practical product delivery.
• Builds side projects, experiments with emerging AI tools, or enjoys hands-on technical exploration.

Bonus Points

• Experience with radar, RF sensing, sensor fusion, computer vision, robotics, or autonomous systems.
• Experience with LangChain, LangGraph, LlamaIndex, AutoGen, Semantic Kernel, or similar frameworks.
• Experience optimizing models for edge deployment using TensorRT, ONNX, OpenVINO, TVM, or similar tools.
• Experience with embedded systems, GPUs, NPUs, FPGAs, or hardware acceleration.
• Familiarity with MLOps, CI/CD, model monitoring, and large-scale production systems.