[Remote] Staff Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Indeed is a job site focused on helping people get jobs and improving the experience for job seekers and employers. The Staff Machine Learning Engineer will lead a workstream on the Employer Agents Team, developing and delivering machine learning and AI projects such as agentic solutions, LLM evaluation capabilities, and ML systems. The role also involves improving LLMOps reliability and infrastructure, guiding technical direction, mentoring engineers, and partnering across teams.

Responsibilities

• 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)

Skills

• 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

Benefits

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

Company Overview

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