Senior ML Platform Engineer – MLOps & GenAI

Credit Acceptance Corporation; San Francisco (CA); Hybrid; USD 185,000 - 259,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Credit Acceptance Corporation seeks an experienced ML Platform Engineer to own end-to-end deployment, model serving, monitoring, and cost analysis for production ML/GenAI systems. You will collaborate with Cloud, Data, Security and SRE to govern gateways, tooling, and observability, ensuring reliability and scalable performance.

Ideal candidates have 5+ years in production ML/AI, strong Python/SQL, and hands-on experience with AWS and Databricks, plus OpenTelemetry observability.

Qualifications

• Bachelor's degree with 7+ years or Master's with 5+ years of relevant experience.
• 5+ years building and operating production ML or AI systems with ownership of at least two areas.
• Strong Python and SQL with production-quality engineering practices (version control, testing, CI/CD).
• Hands-on experience with a cloud ML platform (AWS and Databricks)
• Understanding LLM/GenAI operational considerations (token cost, latency)
• Experience with risk-managed gateway/proxy for agents and tool access
• Containerization and infrastructure as code
• Ability to communicate trade-offs clearly in writing
• Candidates reside in or relocate to SF Bay Area, CA or nearby

Responsibilities

• Own end-to-end deployment path for ML/GenAI models including training, inference, registry, and promotion across dev/QA/production.
• Own runtime health for models in production: monitoring, drift detection, latency/throughput, autoscaling, incident response.
• Operate the agent runtime layer through enterprise gateways and govern tool surfaces.
• Evaluate agents in production: online scoring, drift detection, baselines, release gates.
• Build observability and evaluation pipelines, logs, data contracts.
• Own platform unit economics: cost per inference, per document, per interaction; inform build-versus-buy decisions.
• Deliver reusable pipeline templates and reference implementations for product teams.
• Collaborate with Cloud/Data/Security/SRE for governance, identity, and observability.
• Respond to AI-specific production incidents and drive corrective actions.
• Maintain architecture docs and diagrams for ML platform.
• Mentor engineers and interns on production ML practices.

Skills

Python

SQL

CI/CD

Containerization

AWS

Databricks

MLflow

Kubernetes

LLM/GenAI

Model serving

Observability

OpenTelemetry

Education

Bachelor's degree in CS/Engineering/Statistics

Master's degree in relevant field

Tools

AWS

Databricks

MLflow

Kubernetes

Job description

Credit Acceptance Corporation seeks an experienced ML Platform Engineer to own end-to-end deployment, model serving, monitoring, and cost analysis for production ML/GenAI systems. You will collaborate with Cloud, Data, Security and SRE to govern gateways, tooling, and observability, ensuring reliability and scalable performance.

Ideal candidates have 5+ years in production ML/AI, strong Python/SQL, and hands-on experience with AWS and Databricks, plus OpenTelemetry observability.