Job#: 3054132 Job Description: ML Engineer
Location: Ann Arbor, Michigan (Onsite)
Alternate Location: Remote in the United States, Remote in Canada
Role Overview
We are hiring a Machine Learning Engineer to support the growth of a simulation platform. This role involves working with Autonomy teams to drive adoption from within. You will ensure that model replay and recompute jobs run at scale, that metrics are interpretable, and that engineers can visualize model performance. This position requires you to become an expert on the partnered models, translating between the simulation platform and the autonomy model.
Key Responsibilities
- Act as the embedded point of contact between the Dataloop + Simulation and one to two Autonomy teams, driving hands-on adoption of the simulation platform.
- Implement the end-to-end data flow from the data ops platform to the simulation environment and persistent storage at scale.
- Onboard Autonomy models to execute replay/recompute workflows and 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, such as Camera, Lidar, Vehicle Intent, or Object Tracking, to implement and own integrations.
- Debug issues across the full stack, from data ingestion through simulation execution to storage and metrics.
- Translate feedback from Autonomy engineers into requirements for the product roadmap.
- Document workflows and onboard new users to support scalable adoption.
Required Qualifications
Education: Bachelor's Degree in Computer Science, Robotics, Electrical Engineering, or a related technical field, or a Master's Degree.
Experience: A Bachelor's Degree with 4+ years of experience or a Master's Degree with 2+ years of experience. Experience building or operating data pipelines at scale is required, along with experience in simulation, replay, or model validation.
Technical Skills: Strong Python skills are necessary. Familiarity with autonomy or robotics ML models (perception, tracking, prediction, or planning) and their data is required. Comfort working across cloud storage and compute is also needed.
Preferred Qualifications
- Prior experience in a forward-deployed engineer, solutions engineer, or embedded platform role.
- Hands-on experience with Camera, Lidar, Vehicle Intent, or Object Tracking models.
- Experience with simulation or replay frameworks for autonomous vehicles or robotics.
- Familiarity with visualization tooling such as Foxglove, OpenGL, or Three.js.
- Experience with large sensor data formats (MCAP, Parquet) and associated processing tools (PyArrow, Daft, Pandas).
- Experience with distributed compute/orchestration frameworks (Ray, Anyscale, AWS HyperPods).
- Infrastructure-as-code experience (Terraform) and CI systems (GitHub Actions).
Company Overview & Culture
This organization cares about its team members and strives to provide resources to support their health, work/life balance, and future. The culture is collaborative, energetic, and team-focused. The simulation platform helps Autonomy teams replay, recompute, evaluate, and visualize their models against real and synthetic driving data at scale, turning a logged drive into a repeatable, measurable experiment.
Everforth Apex is a world-class IT services company that serves thousands of clients across the globe. When you join Everforth Apex, you become part of a team that values innovation, collaboration, and continuous learning. We offer quality career resources, training, certifications, development opportunities, and a comprehensive benefits package. Our commitment to excellence is reflected in many awards, including ClearlyRateds Best of Staffing in Talent Satisfaction in the United States and Great Place to Work in the United Kingdom and Mexico.
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