AI ML Engineer

Optum AI is UnitedHealth Group s enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform.

Optum AI team members:
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Primary Responsibilities:

• Develop and deploy innovative AI solutions to various business problems. You will have the opportunity to learn and apply some of the most cutting-edge AI technologies
• Research and evaluate new data sources, AI technology trends and methodologies to enhance Organization level data science capabilities and solutions
• Designing, developing, and maintaining a robust infrastructure to seamlessly deploy, monitor, and manage machine learning models in production environments, bridging the gap between data science and IT operations by ensuring efficient and scalable model deployment and performance tracking; collaborating closely with data scientists to streamline the ML lifecycle through automation and optimization
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelors degree or higher in computer science or engineering with a focus on language processing. 4+ years of overall experience
• Experience with monitoring tools like Prometheus, Grafana
• Experience in deployment of ML based projects
• Experience with MLOps frameworks to design, build, and implement automated ML pipelines using tools like Kubernetes, Docker, and cloud platforms (AWS, Azure, GCP) to streamline model training, deployment, and retraining processes
• Proficiency in programming/scripting languages Python with expertise in relevant ML libraries like Scikit-learn, PyTorch, SQL etc.
• A sound understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering
• Understanding of multiple machine learning techniques such as supervised, unsupervised, reinforcement learning, Deep learning, NLP
• Understanding of Both Opensource and Open AI LLMs and RAG architecture
• Proficiency in effective version control strategies for ML models, data, and code, along with robust logging mechanisms to facilitate debugging and auditing
• Proven ability to design and architect scalable ML systems, considering performance, reliability, and maintainability
• Proven good grasp of using LLMs, Deploying LLMs
• Proven excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions