UnitedHealth Group is looking to solve the problem of building robust, scalable pipelines to ingest and process structured and unstructured data, and to integrate ML insights into orchestration platforms to enable intelligent, self-healing workflows
Requirements
- 5+ years of experience in AI/ML engineering, with a focus on IT operations or infrastructure
- 5+ years of hands-on experience with Python, SQL, and Spark for data processing and model development
- 3+ years of experience with cloud platforms such as Azure, AWS, or GCP
- 3+ years of experience implementing ML Ops practices, CI/CD pipelines, and containerization using Docker and Kubernetes
- 3+ years of experience working with IT operations tools and concepts including CMDB, incident management, and observability platforms
- 2+ years of experience integrating ML models into production environments and supporting model lifecycle management
- 2+ years of experience with NLP, LLM frameworks, and Generative AI techniques
Responsibilities
- Build robust, scalable pipelines to ingest and process structured and unstructured data from tools like Splunk, Dynatrace, ServiceNow, and system logs
- Create and maintain high-quality features for ML models supporting anomaly detection, predictive alerting, and automated remediation
- Collaborate with Data Scientists to operationalize ML models, ensuring they meet performance, scalability, and maintainability standards
- Integrate ML insights into orchestration platforms (e.g., Jenkins, Interlink) to enable intelligent, self-healing workflows
- Design autonomous agents capable of reasoning, planning, and executing tasks across IT operations, handling incident triage, root cause analysis, and resolution
- Uphold data integrity, lineage, and compliance with enterprise security and governance standards
- Leverage cloud-native and hybrid technologies to support real-time analytics and model inference at scale
Other
- Graduate degree in Computer Science, Data Science, or a related field
- Proven solid technical communication skills and experience with collaborative development using GitHub
- Proven ability to work in agile environments and deliver high-impact, scalable solutions
- Experience leading data science projects and mentoring junior team members
- Collaborate with research, engineering, and product teams to translate cutting-edge AI advancements into production-ready capabilities
