Our Mission

Day to Day

As a Senior Machine Learning Engineer on our Sourcing 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 Sourcing product, which connects employers with new talent through AI. This Senior MLE will help us improve our automated outreach quality, building new agentic experiences, and LLMOps reliability and infrastructure.

Responsibilities

• Autonomously deliver ML and AI projects, including prompt development and evaluation, training ML models, building LLM-as-a-Judge capabilities, and building recommendation / ranking systems
• Develop LLM and machine learning model improvements, scale them in production, and run iterative A/B tests to improve our Sourcing product
• 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

Skills/Competencies

• Requires a Bachelor’s degree in Computer Science, Mathematics, or Statistics, 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

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Reference ID: 47061

The deadline to apply to this position is 6/9. Job postings may be extended at the hiring team’s discretion based on applicant volume.

Reference ID: 47061