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Lead AI/ML Engineer
3 months ago
The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best.
Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities.Come make an impact on the communities we serve as you help us advance health equity on a global scale.
Join us to startCaring. Connecting. Growing together.
OptumAI is looking for a Senior Machine Learning Engineer with deep subject matter expertise in text processing, NLU and SLU (Natural language understanding and Spoken Language Understanding) who will be part of a team leading the technical development and inventions that allow Optum machine learning products drive positive impact in the healthcare business.
Your expertise will bring business and industry context to science and technology decisions.As part of the OptumAI AI/ML engineering group, you set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms.
Your code, designs and documents are exemplary and are used as references across the organization.A successful candidate is a hands-on AI/ML engineering expert that will tackle intrinsically hard problems, acquiring expertise as needed. The candidate will help decompose complex problems into straightforward solutions.
Primary Responsibilities:
Help design and develop the next generation of NLP, ML & AI products, and services for healthcare
Develop machine learning and deep learning models and systems in domains including, but not limited to: NLP, NLU, NLG, SLU and multidimensional time series forecasting among others
Exposure in RAG, LangChain, VectorDBs
Ability to Quantize, Optimize GenAI models
Manage NLP & ML models lifecycle for a suite of products
Run large complex proof-of-concepts for the healthcare business
Manage prioritization and technology work for building NLP, ML & AI solutions
Lead the full end-to-end machine learning development process including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation
Establish best practices for end-to-end deep learning and machine learning development cycle to ensure rigor in process and quality in outcome
Work with a great deal of autonomy to find solutions to complex problems
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 soRequired Qualifications:
Undergraduate degree in applicable area of expertise or equivalent experience
Experience in deploying scalable solutions to complex problems, from defining the problem, implementing the solution, and launching the new product successfully
Skill Set; NLP, NLU, NLI
Architecture:
Transformers, Attention
Models:
GPT, Llama, Mistral
Model Quantization
Model Optimization
Retrieval & Ranking, RAG, RAGAS
Statistics, Machine Learning Models, Model Deployment
Proven excellent communication, writing and presentation skills
Experience in the health care industry
Preferred Qualification:
Experience in the health care industry
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone.
We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life.Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes.
We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.
