Machine Learning Engineer, Genies

• ▸ Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field
• ▸ 2+ years of hands-on experience building agentic systems with Large Language Models (LLMs)
• ▸ 3+ years building scalable, production-grade backend systems in Python (Go or JavaScript also welcome)
• ▸ 5+ years of experience in machine learning and statistics, with a track record of shipping products that leverage LLMs, ML, CV, or NLP models
• ▸ Strong communication skills and demonstrated experience collaborating directly with product teams to design and elevate AI-driven features
• ▸ A proactive approach to learning — you follow emerging AI research and bring what matters back to the team

Desirable

• We are seeking a highly motivated and passionate Machine Learning Engineer to join our core AI team in San Francisco, CA
• This is a high-impact role where you will take end-to-end ownership of the research and development behind our core AI avatar chat systems
• You will drive the technical roadmap that defines the intelligence, personality, and interactivity of millions of AI avatars
• By tackling fundamental technical challenges, you will bring fun, autonomous, and inspiring AI companions to life
• Working alongside a dedicated team of engineers and researchers, you will bridge the gap between cutting-edge AI research and real-world, consumer-facing product impact
• ▸ Research and implement state-of-the-art AI solutions. You'll apply foundation models, prompt engineering, RAG, knowledge graphs, and multi-agent architectures — alongside classical ML techniques — to power a multimodal AI avatar product
• ▸ Architect and deliver scalable agentic systems. You'll design and implement AI features within our backend, building agent infrastructure that is reliable, extensible, and ready for production scale
• ▸ Translate research into production. You'll work closely with AI researchers to seamlessly bridge the gap between experimental outputs and robust, maintainable backend systems — keeping quality high at both ends of the pipeline
• ▸ Partner with Product on what actually ships. You'll collaborate directly with the product team to iterate on AI systems based on user feedback and engagement metrics, shaping features that users feel
• ▸ Design and execute rigorous evaluation frameworks. You'll build quantitative benchmarks to continuously measure and improve agentic system quality — defining what 'good' looks like for avatar intelligence at Genies
• ▸ Own AI quality, safety, and cost. You'll define, implement, and enforce best practices for agent quality assurance, safety guardrails, and inference cost control — critical disciplines for a production AI system at scale
• ▸ Fine-tine and train models when off-the-shelf falls short. You'll identify gaps in existing foundation models and lead fine-tuning or training efforts to close them
• ▸ Stay at the frontier. You'll actively track academic and industry research in LLMs and AI agents, prototype novel techniques, and bring what's relevant into the team's technology stack