Senior Robotics AI Engineer
Team: Perception, Planning, and Controls
Location: Philadelphia, PA
Commitment: Full Time
Workplace Type: onsite
Responsibilities
- Own the development and productionization of ML systems, including model design, training, fine tuning, optimization, deployment and continuous improvement.
- Develop and adapt models across multimodal inputs (e.g., camera, LiDAR) and other AI domains as product needs evolve.
- Integrate ML outputs into the robotics stack, ensuring reliable performance under real-time and hardware constraints.
- Investigate customer reported issues and drive root-cause analysis to improve system robustness.
- Build and improve infrastructure for rapid experimentation, model iteration, evaluation and deployment.
- Improve and scale data collection, labeling, preprocessing and validation pipelines to ensure high-quality training datasets.
- Implement robust simulation and field testing workflows, along with production monitoring to detect drift and performance degradation.
- Collaborate cross-functionally with Product and Engineering to translate requirements into scalable AI solutions.
- Master’s degree or PhD in Robotics, Computer Science or a related technical field.
- 4+ years of professional experience in developing software for robotics and machine learning.
- Strong proficiency in Python and C++.
- Experience using ML frameworks like TensorFlow, PyTorch, or similar
- Proven experience building, deploying and maintaining ML models in production, ideally on edge systems.
- Hands-on experience working with camera and LiDAR data for perception and navigation tasks.
- Experience with ML optimization and acceleration tools (e.g., TensorRT), including familiarity with quantization, pruning and other model compression techniques.
- Strong problem solving mindset and comfort working across system boundaries.
- Ability to clearly communicate complex advanced concepts to both technical and non-technical stakeholders.
- Continual learning mindset and staying updated with the latest ML research and methodologies.
Nice To Haves
- MLOps Experience (experiment tracking, dataset versioning)
- Proficiency in ROS
- Familiarity with Docker, Linux and production infrastructure environments
Perks
- Competitive salary and benefits package (medical/dental/vision)
- Early-Stage Equity
- 401K Plan
- Unlimited PTO
- Paid parental leave
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