Staff ML Platform Engineer - GenAI & Production ML

Credit Acceptance Corporation; Bellevue (WA); Hybrid; USD 185,000 - 259,000; Full time

Job summary

Credit Acceptance is seeking a seasoned ML/GenAI platform engineer in Bellevue, WA. You will own end-to-end ML/GenAI deployment, monitor production health, and drive governance for enterprise AI surfaces.

You will collaborate with Cloud, Data, Security, and SRE teams, shaping the future of AI at Credit Acceptance. The role requires strong Python/SQL, AWS/Databricks experience, and a proven track record in production ML systems.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics or a relevant technical field with at least 7 years of relevant experience.
• 5+ years building and operating production ML/AI systems, with direct ownership of at least two areas (training/inference pipelines, model serving, registry/versioning, monitoring).
• Proven ownership of a production ML/AI service through its full operating life: deployed, monitored, paged, diagnosed, fixed.
• Strong Python and SQL, with production-quality engineering practices (VCS, testing, code review, CI/CD).
• Hands-on experience with a cloud ML platform in production (AWS and Databricks preferred; model serving, orchestration, registry/experiment tracking such as MLflow).
• Knowledge of how LLM/GenAI workloads differ operationally from traditional ML.
• Experience running LLM/agent apps behind a gateway/proxy and building best practices for routing, credentials, rate-limiting, and budgets.
• Knowledge of containerization and infrastructure as code.
• Ability to communicate technical trade-offs clearly in writing to engineers and non-engineers.
• Candidates must reside in or relocate to hub locations: Southfield MI, Bellevue WA, or SF Bay Area CA.

Responsibilities

• Own deployment path for ML and GenAI models end to end: training/inference pipelines, registry/versioning, serving endpoints, and promotion across dev/QA/prod.
• Own runtime health for models in production: monitoring, drift detection, latency/throughput targets, autoscaling, incident response and root-cause actions.
• Operate the agent runtime layer via enterprise gateways, migrate agents to governed paths with least-privilege surfaces.
• Own evaluation of agents in production with online scoring, baselines, drift detection, and release-gate mechanics.
• Build and maintain observability and evaluation substrate: traces, telemetry, logging, pipelines, and data contracts.
• Own platform unit economics: cost per inference/document/interaction and cost analyses for build-vs-buy and hosting decisions.
• Make the paved road real: reusable pipelines/templates, reference implementations, internal tooling.
• Partner with Cloud/Data/Security/SRE to embed ML platform in governance and identity systems.
• Respond to AI-specific production incidents and close corrective actions (injections, rogue costs, data exposure).
• Maintain architecture docs and diagrams for the ML platform.
• Mentor engineers and interns in production ML practices and enforce quality through design/code review.

Skills

Python

SQL

AWS

Databricks

Model serving

Containers

CI/CD

GenAI concepts

Communication

Education

Bachelor's degree in CS/Engineering/Statistics or relevant field

Master's degree with 5+ years relevant experience

Tools

MLflow

Job description

Credit Acceptance is seeking a seasoned ML/GenAI platform engineer in Bellevue, WA. You will own end-to-end ML/GenAI deployment, monitor production health, and drive governance for enterprise AI surfaces.

You will collaborate with Cloud, Data, Security, and SRE teams, shaping the future of AI at Credit Acceptance. The role requires strong Python/SQL, AWS/Databricks experience, and a proven track record in production ML systems.