Lead Engineer, Machine Learning

sephora.com•Fresno, CA

2d•Remote

About The Position

Ready for a career glow up? As a Lead Machine Learning Engineer, you'll be the driving force behind the architecture, engineering, and deployment of cutting-edge AI/ML systems at enterprise scale. The work you do will impact beauty, as you redefine how we inspire and connect with our customers — building the next generation of intelligent, AI-powered experiences across the beauty space. You'll lead a team that's united in beauty, supported by those who are equally passionate about pushing the boundaries of applied AI, engineering excellence, and real-world product impact.

Requirements

5+ years hands-on experience in model development, training pipelines, feature stores, model serving, and MLOps/LLMOps — with a proven ability to take systems from experimentation to production at scale.
8+ years proficiency in Python, distributed systems, API design, and cloud-native architectures, with a strong command of engineering best practices including CI/CD, testing, and observability.
3+ years proven experience building and deploying LLM-powered applications, including RAG pipelines, prompt engineering, fine-tuning, and evaluation frameworks.
Hands-on experience with Agentic AI frameworks such as LangChain, LangGraph, Claude, or similar, with the ability to architect and engineer production-grade multi-agent systems.
Strong understanding of supervised/unsupervised learning, recommendation systems, reinforcement learning, and model evaluation methodologies.
Experience with Kubernetes, Docker, Databricks, MLflow, Vector databases, and cloud platforms (AWS, GCP, or Azure).
A passion for exploring new ideas, staying current with the latest advancements in AI/ML, and solving complex engineering challenges at scale — bringing those insights back to elevate the team.
Excellent communication skills with the ability to align stakeholders, influence technical direction, and drive clarity across engineering, product, and business teams.

Responsibilities

Architect & Engineer Production-Grade AI/ML Systems. Design, build, and maintain scalable ML and Agentic AI systems using established engineering design patterns. Lead security-first and reliability-first practices, maintain deep domain expertise in ML systems and LLM infrastructure, and proactively anticipate future technical needs, scalability requirements, and cost implications.
Own End-to-End ML Solutions. Engineer and own batch and real-time model serving, agentic pipelines, RAG systems, and LLMOps infrastructure. Build and maintain robust tooling for monitoring, observability, logging, automated testing, performance testing, and A/B experimentation to ensure production reliability and continuous improvement.
Establish & Optimize ML Pipelines. Build scalable, efficient, and automated pipelines for data processing, feature engineering, model development, validation, evaluation, and deployment — ensuring reproducibility, quality, and operational excellence across the full ML lifecycle.
Deliver High-Quality Code in a Continuous-Release Environment. Write clean, efficient, and well-structured code to deliver AI/ML products iteratively. Uphold high engineering standards including code reviews, CI/CD integration, and test coverage across ML services and agentic workflows.
Partner Cross-Functionally to Shape AI/ML Capabilities. Collaborate closely with Product, Engineering, Data Scientists, ML Engineers, and Business stakeholders to define, scope, and plan new AI/ML capabilities — translating business requirements into technically sound, scalable engineering solutions.
Drive Delivery Planning & Engineering ROI. Review and prioritize epics and projects with clear breakdown, dependency management, and delivery planning. Proactively identify, communicate, and resolve blockers or delays. Navigate ambiguity and high-pressure situations with decisiveness, applying economic thinking to maximize value delivery.
Mentor, Grow & Inspire the Team. Mentor and develop ML Engineers and Data Scientists by promoting best practices in ML engineering, code quality, and operational excellence. Foster a culture of effective communication, continuous feedback, and knowledge sharing. Build strong cross-functional relationships and actively contribute to engineering strategy and the AI/ML product roadmap.

Benefits

medical, dental, and vision coverage
disability and life insurance
401k with 4% match
FSA and HSA programs
Student Debt Retirement plan
PTO
flexibility
protected leave
access to training, development, and tuition reimbursement
30% discount on all merchandise/services
opportunities for free product or “gratis”
flash sale discounts on LVMH brand products
free mental health and financial coaching resources with 24/7 access to Modern Health and Financial Finesse
volunteer and donation matching