Top Machine Learning Engineer Jobs in Lexington, KY

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Lead development and deployment of machine learning and analytics products for mortgage lending. Design data pipelines, ensure data quality, build predictive models, communicate insights, mentor junior staff, and partner with engineering and DevOps for scalable MLOps solutions.

Design, build, and deploy end-to-end production ML systems for audience targeting, lookalike generation, and propensity scoring. Own ML lifecycle from experimentation to production monitoring, leverage distributed/cloud platforms, implement vector similarity and embedding systems, engineer scalable features, and collaborate with engineering and product teams to ensure model quality and operational reliability.

As a Senior Vice President at AlixPartners, you will lead complex projects focusing on performance improvement, data analysis, and machine learning applications to enhance business outcomes.

The AI Engineer II will develop and deploy machine learning solutions in healthcare, mentor junior staff, and work on complex data analytics to improve patient care and operational efficiencies.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

As an AI Consultant, you will collaborate with clients to design, build, and deploy end-to-end AI/ML solutions while leveraging your expertise in data science and machine learning.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.