Senior Machine Learning Engineer

Indeed•Remote,

1d•$138,000 - $289,000

About The Position

As a Senior Machine Learning Engineer on our Employer Agents team, you will work on developing and deploying ML and AI solutions in production. You'll be collaborating with a cross-functional product team to drive value and better customer experiences for our employer-facing Agentic solutions, helping redefine the employer hiring journey through AI. This Senior MLE will help us build new agentic experiences, and drive improvements in our LLMOps reliability and infrastructure.

Requirements

Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 5 years of related experience; or a Master’s degree with a minimum of 3 years of experience; or a PhD without experience
Prior success in deploying impactful Machine Learning and/or LLM-based solutions to large-scale production systems
Solid knowledge of data structures and algorithms
Demonstrated sense of ownership and accountability as a key contributor in the technical and product domains
Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
Knowledge of and practical experience working on Deep Learning libraries (like Torch, Tensorflow, etc.) and modern ML/LLM tooling
Familiarity with modern ML system design, including evaluation, experimentation, and production monitoring for predictive and LLM-based systems
Excellent written and verbal communication, effective with technical and business audiences

Responsibilities

Autonomously deliver ML and AI projects, including prompt development and evaluation, building LLM-as-a-Judge capabilities, and building ML systems and models
Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our employer-facing AI solutions
Estimate potential business impact of AI and ML and balance tradeoffs between delivery velocity and systematic infrastructure investments
Collaborate with cross-functional partners, including Machine Learning Engineers, Data Scientists, Software Engineers, Product, and UX designers/researchers
Define and implement evaluation, observability, and production monitoring approaches for ML and LLM-based systems.
Serve as a trusted partner and communicator for cross-functional and cross-team counterparts, translating technical concepts to facilitate productive collaboration.
Mentor other Machine Learning Engineers, Data Scientists, and Software Engineers on the team