Senior ML / AI Engineer

Responsibilities

Architect and build machine learning and retrieval systems for core product experiences. Collaborate with cross-functional teams to design data pipelines and develop scalable inference infrastructure.

Requirements

Requires at least 5 years of experience in consumer AI or ML systems with a proven track record of shipping features. Candidates must have a degree in computer science, mathematics, electrical engineering, or a related field.

Skills

• Machine Learning
• Artificial Intelligence
• Python
• FastAPI
• PostgreSQL
• Vector Databases
• Embeddings
• LLMs
• RAG
• NLP
• Data Pipelines
• Inference Infrastructure
• Recommendation Systems
• Ranking
• Search
• Personalization

Benefits

• Visa sponsorship

About this role

About the Role
Join a small, senior engineering team building the ML systems behind consumer-facing products. You will shape the data pipelines, models, retrieval systems, and inference infrastructure that make intelligent product features useful and intuitive.
What You'll Do
Architect and build machine learning and retrieval systems for core product experiences.
Design data pipelines to ingest, classify, enrich, and summarize user data.
Develop scalable inference infrastructure for real-time and batch workloads.
Guide model selection, fine-tuning, embeddings, RAG pipelines, evaluation frameworks, and quality measurements.
Prototype new ML-powered product ideas and strengthen successful approaches for production.
Collaborate with product, design, and engineering to deliver polished user-facing features.
Establish strong practices for ML development and system quality across the team.
What We're Looking For
At least 5 years of software or machine learning engineering experience in consumer AI or ML systems.
Experience building and shipping ML-powered features from early development to real users, such as personalization, ranking, search, or recommendations.
Background working from consumer needs to determine and build the right ML capabilities.
Hands-on experience developing custom models, including embeddings, recommendation, or personalization models.
Knowledge of LLMs, RAG, classification, NLP, retrieval systems, data pipelines, and inference infrastructure.
Experience with Python, FastAPI, PostgreSQL, vector databases, and embeddings.
A degree in computer science, mathematics, electrical engineering, or a related field, with clear career growth and experience in entrepreneurial or startup environments.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is available.
Location
On-site in San Francisco, California, United States.