MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- ML Engineer scaling Torc Robotics’ simulation platform for autonomous trucks. Embedding with Autonomy teams to operationalize replay, recompute, metrics, visualization, and model integrations.
Responsibilities
- Act as the embedded point of contact between Dataloop + Simulation and one to two Autonomy teams, driving hands-on adoption of Torc Sim
- Implement the end-to-end data flow from the data operations platform through the simulation environment to persistent storage at scale
- Onboard Autonomy models to execute replay/recompute workflows at scale and perform subsequent metric evaluation
- Ensure adoption of visualization tooling and provide UI/UX improvements for the development backlog
- Become a domain expert on partner-team models and own their integrations
- Debug issues across data ingestion, simulation execution, storage, and metrics, driving them to resolution
- Translate feedback from Autonomy engineers into concrete requirements for the Dataloop + Simulation product roadmap
- Document workflows and onboard new users so adoption scales beyond hands-on support
Requirements
- Bachelor's Degree in Computer Science, Robotics, Electrical Engineering, or a related technical field plus competencies typically acquired through 4+ years of experience, OR Master's Degree plus 2+ years of experience
- Strong Python skills
- Experience building or operating data pipelines at scale
- Experience with simulation, replay, or model validation
- Familiarity with autonomy or robotics ML models and their data
- Comfort working across cloud storage and compute
- Strong cross-team communication skills
- Hands-on problem-solving ability
- Bonus: prior forward-deployed engineer, solutions engineer, or embedded platform experience
- Bonus: experience with Camera, Lidar, Vehicle Intent, or Object Tracking models
- Bonus: experience with autonomous-vehicle or robotics simulation/replay frameworks
- Bonus: familiarity with Foxglove, OpenGL, or Three.js
- Bonus: experience with MCAP, Parquet, PyArrow, Daft, or Pandas
- Bonus: experience with Ray, Anyscale, or AWS HyperPods
- Bonus: Terraform and GitHub Actions experience
Benefits
- A competitive compensation package that includes a bonus component and stock options
- 100% paid medical, dental, and vision premiums for full-time employees
- 401K plan with a 6% employer match
- Flexibility in schedule
- Generous paid vacation available immediately after start date
- Company-wide holiday office closures
- AD+D and Life Insurance
- Potential sign-on payments, relocation, and other forms of compensation as part of the total compensation package
- Medical, financial, and/or other benefits
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