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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and evaluating LLM agents and ML systems, with a strong focus on technical leadership, mentorship, and the ability to translate research into reliable production systems. Proficient in software engineering practices and disciplined AI usage to ensure high-quality outputs.
Highest-signal resume keywords
LLM Agent DevelopmentMachine Learning FundamentalsTechnical LeadershipSoftware Engineering SkillsMentorship and Technical Quality Improvement
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningLLM DevelopmentRepresentation LearningRecommendation SystemsGenerative Retrieval ModelsExperiment EvaluationTechnical ReviewsSystem DesignCode ImplementationData Analysis
Soft Skills
Clear CommunicationMentorshipDecision-Making Under Ambiguity
Tools & Technologies
ML Development InfrastructureProduction SystemsEvaluation Frameworks
Industry Keywords
Automated Recommendation ResearchAgentic AI SystemsSemantic ID LearningExperimentationTechnical Quality
About the role
Key responsibilities & impact- Own and advance a major technical area in automated recommendation research within Reflex
- Build LLM agents that connect hypothesis generation, implementation, experiment execution, evaluation and learning from previous results
- Develop rigorous evaluations for agent behavior and research outputs
- Contribute to generative retrieval models, particularly Semantic ID learning, evaluation and production integration
- Take research ideas and prototypes through offline evaluation, online experimentation and production launches
- Build reliable integrations with ML development infrastructure
- Make tradeoffs across model quality, iteration speed, compute cost and operational complexity
- Improve technical quality through implementation, design and code reviews, documentation and mentorship
- Work with research, recommendation and ML infrastructure teams to shape approaches, resolve dependencies and support adoption
- Identify relevant research advances and contribute new methods where needed
Requirements
What you’ll need- Bachelor's in Computer Science, Machine Learning or a related field, or equivalent practical experience
- Minimum 8 years of experience building and shipping ML or AI systems, including substantial hands-on engineering and technical leadership
- Experience building LLM agents or other agentic AI systems for complex tasks
- Clear approach to evaluating and improving agent performance
- Strong ML fundamentals and depth in applied LLMs, representation learning, recommendation systems, retrieval or ML systems
- Experience taking research ideas into reliable production systems and evaluating their impact through meaningful experiments
- Strong software engineering skills, including designing maintainable systems, implementing difficult components and conducting thorough technical reviews
- Experience leading a substantial technical area and making decisions under ambiguity
- Track record of mentoring engineers and raising technical quality
- Clear written and verbal communication
- Disciplined use of AI, including verification of generated code, analysis and conclusions
- US-based applicants only
Benefits
Comp & perks- Equity eligibility
- Flexible working model
- Continued growth as a technical leader
- In-person collaboration 1–2 times per quarter rather than daily office attendance
- Relocation assistance is not provided