AI or ML Engineer - Remote

Role

Optum is seeking an AI/ML Engineer to build and operate scalable machine learning and generative AI platforms across the enterprise. The role focuses on designing and implementing ML infrastructure, model lifecycle management, and MLOps/LLMOps pipelines to support reliable experimentation, deployment, monitoring, and governance of ML and LLM systems.

Key Responsibilities

• Build enterprise ML and GenAI platforms supporting experimentation, model training, evaluation, deployment, monitoring, and lifecycle management.
• Productionize machine learning and generative AI models using batch and real-time inference architectures.
• Design and operate MLOps and LLMOps pipelines, including CI/CT/CD workflows for model testing, validation, versioning, and promotion across environments.
• Develop scalable, cloud-native ML infrastructure using Docker, Kubernetes, and managed cloud ML platforms (e.g., SageMaker, Azure ML, Vertex AI).
• Build and manage LLM application stacks including gateways, orchestration layers, model routing, caching, and cost/performance optimization.
• Implement model monitoring and lifecycle management systems to track drift, latency, bias, and data quality and enable automated retraining.
• Ensure governance, security, and compliance of ML systems (lineage, auditability, reproducibility, observability).
• Collaborate with data scientists, data engineers, and software engineers to define production ML standards and scalable AI solutions.

Requirements

Required

• 5+ years experience in machine learning engineering, MLOps, or AI platform engineering building production ML systems and scalable model pipelines.
• 4+ years programming in Python for ML systems and familiarity with frameworks such as PyTorch, TensorFlow, or scikit-learn.
• 3+ years working with ML lifecycle platforms such as MLflow, Kubeflow, SageMaker, Azure ML, or GCP Vertex AI.
• 3+ years building cloud-native ML platforms using Docker, Kubernetes, and distributed systems.
• 3+ years with distributed data processing and orchestration tools such as Spark, Ray, Airflow, Dagster, or Prefect.
• 3+ years experience with Generative AI and LLMs, including prompt engineering, prompt chaining, and fine-tuning (instruction tuning and LoRA/qLoRA).

Preferred

• Master’s degree in Computer Science, Engineering, Data Science, or related discipline.
• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).
• Experience in regulated or enterprise environments with emphasis on security, compliance, and responsible AI.
• Experience with vibe-coding tools such as Cursor, Claude Code, and Replit.
• Experience operating multi-cloud or hybrid ML platforms, knowledge of LLM cost optimization and performance tuning, exposure to knowledge graphs or hybrid search, and contributions to open-source ML or MLOps tooling.

Location & Work Arrangement

• Remote from anywhere within the U.S.; hires in Minneapolis or Washington, D.C. must work in-office a minimum of four days per week.
• Telecommuter policy applies for remote employees.

Compensation & Benefits (excerpt)

• Salary range: $98,547 to $175,978 annually (based on full-time employment).
• Benefits include a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and 401(k) contribution.