Senior Machine Learning Engineer, AI Agent
GeniesGenies San Francisco$200k – $275kPosted 26 March 2026
Job Description
Senior Machine Learning Engineer, AI Agent
Genies is an avatar technology company powering the next era of interactive digital identity through Smart Avatars. With the Avatar Framework and intuitive creation tools, Genies enables developers, talent, and creators to generate and deploy game-ready Smart AI companions. The company’s technology stack supports full customization, AI-generated fashion and props, and seamless integration of user-generated content (UGC). Backed by investors including Bob Iger, Silver Lake, BOND, and NEA, Genies’ mission is to become the visual and interactive layer for the LLM-powered internet.
About the Role:
We are seeking a highly motivated and passionate Senior 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.
What You'll Be Doing:
- Research and implement state-of-the-art solutions using foundation models, prompt engineering, RAG, knowledge graphs, and multi-agent architectures, alongside classical machine learning techniques for a multi-modal AI chat product.
- Architect, implement, and deliver scalable AI features and agentic systems within our backend systems.
- Design and execute rigorous quantitative benchmarks to evaluate and continuously improve agentic systems and AI features.
- Partner with the product team to iterate on and refine AI systems based on user feedback and engagement metrics.
- Work closely with AI researchers to seamlessly transition experimental research outputs into robust, production-ready backend systems.
- Define, implement, and enforce best practices for AI agent quality assurance, safety, and cost control.
- Fine-tune and train LLM/ML models when off-the-shelf options are inadequate.
- Remain at the forefront of academic and industry research in LLMs and AI agents, actively identifying and prototyping novel techniques to advance our technology stack.
What You Should Have:
- Master’s or Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field.
- 2+ years of hands-on experience developing agentic systems utilizing Large Language Models (LLMs).
- 3+ years of experience building scalable, production-grade backend systems in Python (or Go, Javascript).
- 5+ years of experience in machine learning and statistics, with a proven track record of building products leveraging LLMs, ML, CV, or NLP models.
- Strong communication skills, with demonstrated experience collaborating directly with product teams to design and elevate AI-driven features.
- A proactive approach to learning, staying informed by taking an active interest in emerging AI research and industry trends.
What We Prefer
- Master’s degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- 3+ years of specialized experience developing complex, multi-agent systems using LLMs.
- Strong product intuition and a refined taste for delivering exceptional user experiences.
- Comfort thriving in a lean, fast-moving team environment; a willingness to dive in, take bold initiative, and own complex problems.
- A genuine passion for shipping products that surprise, delight, and engage users.
- A track record of publishing research at top-tier AI/ML conferences (e.g., ACL, NeurIPS, ICML, ICLR, AAAI, EMNLP, NAACL).
The base salary for this position will vary based on several factors, such as relevant experience, location and your approved inte ... (truncated, view full listing at source)
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