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# ML Engineer

- **Company:** Everforth Apex
- **Location:** Ann Arbor, MI, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computer Vision, Cloud Storage, Software Debugging, Github, Design of User Interfaces, Python (Programming Language), Machine Learning, OpenGL, Data Streaming, Parquet, Three.js, Data Ingestion, Model Validation, Pandas, Kubernetes, Information Technology, Terraform, Lidar, Data Pipelines
- **Published:** October 5, 2026
- **Apply:** https://www.dice.com/job-detail/2582abe1-7911-4628-b2f0-44986e309c7c

## About the Role

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).

## Description

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., * 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.