Senior AI ML Engineer Hybrid
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Required Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience) 3+ years of professional software development experience with Java or Python or C# or JavaScript or C++ 2+ years of experience with Azure or AWS or GCP. and Terraform for cloud infrastructure provisioning 2+ years of experience with Kubernetes and Docker; familiarity with containerized microservices, deployment manifests, and container orchestration Solid experience with relational databases, including SQL Server or PostgreSQL, plus Elasticsearch for search/indexing Experience with OpenAI or similar LLM APIs; hands-on prompt engineering, managing prompts, guardrails, and cost controls Experience with AI model training pipelines (data collection/labeling, fine-tuning/adaptation, evaluation) and integrating trained models into production workflows Knowledge of security best practices for cloud-native apps, secrets management, and data privacy Preferred Qualifications Certification in cloud or container technologies (e.g., Azure: AZ-204/AZ-400, Kubernetes CKAs/CKADs, Terraform Associate) Experience with Azure OpenAI Service or other OpenAI alternatives; familiarity with cost management for AI workloads Experience with observability and SRE practices, including distributed tracing and incident response Experience contributing to developer tools or developer experience products Git / GitHub / GitHub Apps experience; building or consuming automations, apps, or actions to integrate with development workflows Proven excellent problem-solving, communication, and collaboration skills; ability to work effectively with cross-functional teams All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc.