Staff Machine Learning Engineer

Role Description

As a Staff Machine Learning Engineer, you will be a team lead on the Employer Agents Team. Your team will be responsible for driving value and better customer experiences for our employer-facing Agentic solutions, helping redefine the employer hiring journey through AI. You will own one of the team's major workstreams, partner with cross-functional teams to develop and deliver ML and AI projects, including:

• Agentic solutions
• LLMs-as-a-Judge
• Evaluation capabilities
• ML systems and models

You will help drive technical direction for the team while guiding other members to achieve product and technical goals. On a daily basis, you will:

• Explore data
• Formulate problem statements
• Build new agentic experiences
• Drive improvements in our LLMOps reliability and infrastructure

Qualifications

• Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with 3 years experience
• Familiarity with agent orchestration frameworks, LLM observability tools, and prompt optimization techniques (e.g. GEPA)
• Prior success in deploying impactful Machine Learning solutions to large-scale production systems, while partnering across teams
• Solid knowledge of data structures and algorithms
• Sense of ownership and accountability as a key contributor in the technical and product domains
• Knowledge and practical experience working on Deep Learning Libraries (like Torch, Tensorflow, etc.)
• Excellent written and verbal communication in English, effective with technical and business audiences

Requirements

• Partner with cross-functional teams to enhance and optimize search algorithms for improved accuracy, relevance, and overall user experience
• Experiment with Proof of Concept Machine Learning model improvements, scale them to production, and run iterative A/B experiments to improve our matching technology while partnering with other teams
• Define and clarify project priorities, deliverables, and success criteria in partnership with cross-functional teams
• Act as a bridge between technical and non-technical collaborators, facilitating effective communication and comprehension of project goals and outcomes
• Mentor and grow other software engineers and Machine Learning Engineers across teams
• Break down larger Machine Learning initiatives into pieces that deliver incremental business value and guide the team through implementing them
• Represent Indeed at major Machine Learning conferences, such as Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR)

Benefits

• Quarterly bonuses
• Restricted Stock Units (RSUs)
• Paid Time Off policy
• Region-specific benefits