Senior Machine Learning Engineer
Livonia, Michigan, United States of America
Full Time
1 hour ago
Visa Sponsor
Key skills
PythonPyTorchScikit-LearnTensorflowAIMachine LearningMLNLPGenerative AIGenAILarge Language ModelsRAGAgenticTensorFlowscikit-learnMLOpsCommunication
About this role
Role Overview
- Develop and coach individual MLE’s.
- Effectively balance multiple projects and provide guidance to MLE’s on best practices and aligning with organizational objectives.
- Architecting solutions to solve business problems.
- Partnering with Business Units to assess and implement vendor AI tools.
- Assessment of intellectual property and company assets utilized by partners with their AI tools.
- Design and implement intelligent systems using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to enhance operational efficiency and decision-making.
- Develop AI agents that assist internal teams (e.g., Claims, Underwriting, Member Services) with tasks like summarization, document processing, and knowledge retrieval.
- Partner with strategic vendors and platform providers to explore and integrate enterprise-grade GenAI capabilities into AAA Life’s ecosystem.
- Translate business problems into practical AI solutions, leveraging internal data and LLMs to create scalable tools.
- Implement and refine MLOps practices to support the deployment and monitoring of AI agents and services.
- Collaborate with stakeholders across operations, IT, and automation to align AI initiatives with business goals.
- Mentor junior engineers and advocate for best practices in responsible, sustainable AI implementation.
Requirements
- Bachelor’s degree in a quantitative discipline (Computer Science, Engineering, Statistics, etc.) or related field and 7+ years of hands-on experience developing and deploying machine learning models in production.
- OR Master’s degree in a quantitative discipline (Computer Science, Engineering, Statistics, etc.) or related field and 5+ years of hands-on experience developing and deploying machine learning models in production.
- Experience working with NLP and/or large language models (LLMs).
- Excellent communication skills and ability to explain ML results to non-technical audiences.
- Strong knowledge of MLOps tools and model monitoring.
- Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
Tech Stack
- Python
- PyTorch
- Scikit-Learn
- Tensorflow
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Professional development opportunities