AI Summary
Jobgether is seeking a Senior Machine Learning Integration Engineer to optimize and maintain ML-driven motion planning and control algorithms for vehicles. The role requires close collaboration with motion planning, control, perception, and software engineering teams. The ideal candidate will have hands-on experience deploying ML systems on real-world robotics, embedded, or autonomous platforms.
Key Highlights
Deploy ML-based motion planning and control models onto vehicle platforms
Optimize models for inference speed, latency, and resource efficiency
Integrate ML components with motion planning, controls, and perception systems
Build scalable deployment infrastructure for ML models
Maintain production-quality code in C++ and Python
Technical Skills Required
Benefits & Perks
Competitive salary range: $142,000 – $225,000 USD
Fully remote work environment
Comprehensive medical, dental, and vision coverage
401(k) plan with company match
Life and disability insurance options
Professional development and education allowances
Pet insurance
Wellness stipends
Home office support
Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Engineer/Senior Machine Learning Integration Engineer in the United States.
This role offers the opportunity to directly impact the deployment of advanced machine learning models in real-time autonomous systems. The Engineer/Senior Machine Learning Integration Engineer will focus on optimizing and maintaining ML-driven motion planning and control algorithms for vehicles, ensuring safety, reliability, and performance under resource constraints. The role requires close collaboration with motion planning, control, perception, and software engineering teams to integrate ML components seamlessly into production systems. Candidates will work on scalable deployment infrastructure, including benchmarking, model packaging, automated validation, and iterative improvements. This position is ideal for technically strong, problem-solving engineers passionate about autonomous systems and real-world ML applications in safety-critical environments.
Accountabilities
- Deploy ML-based motion planning and control models onto vehicle platforms, ensuring performance under computational and memory constraints.
- Optimize models for inference speed, latency, and resource efficiency without compromising accuracy or safety.
- Integrate ML components with motion planning, controls, and perception systems in the autonomous driving stack.
- Build scalable deployment infrastructure, including evaluation pipelines, model packaging, benchmarking, and automated validation.
- Validate model performance through both simulation and on-road testing, analyze results, and iterate on improvements.
- Maintain production-quality code in C++ and Python, following modern software development practices.
- Collaborate across teams to ensure models meet strict performance and safety requirements.
- BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Hands-on experience deploying ML systems on real-world robotics, embedded, or autonomous platforms.
- Strong software engineering skills in C++ and Python, including testing, code reviews, and CI/CD practices.
- Experience with ML frameworks such as PyTorch or TensorFlow, including model optimization for deployment.
- Familiarity with GPU acceleration and inference optimization tools like TensorRT or CUDA.
- Strong problem-solving skills with the ability to debug complex systems under production constraints.
- Bonus: experience with autonomous vehicle motion planning and control algorithms (MPC, LQR, PID), ROS, AUTOSAR, reinforcement learning methods, or publications in relevant ML/robotics conferences.
- Competitive salary range: $142,000 – $225,000 USD, with potential bonus and equity.
- Fully remote work environment.
- Comprehensive medical, dental, and vision coverage.
- 401(k) plan with company match.
- Life and disability insurance options.
- Professional development and education allowances.
- Additional perks such as pet insurance, wellness stipends, and home office support.
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.