Machine Learning Engineer

San Francisco

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FERMÀT is the AI native commerce platform that optimizes shopping experiences, leading to best-in-class shopper engagement and conversion. We help brands transform clicks into conversions with dynamic, personalized shopping experiences—built and optimized in minutes.

Backed by VMG, Bain Capital Ventures, Greylock, QED, and named The Information’s #1 commerce startup, we’re a 70+ person team based in SF, Austin, NYC, and Bangalore. As a fast-growing Series B company, we’re building the infrastructure for the future of online retail—and we’re just getting started.

About the Role:

We’re searching for a visionary Machine Learning Engineer to join FERMÀT as the founding member of our AI/ML team. This is your chance to shape Pierre, FERMÀT's AI Agent, from the ground up—an intelligence engine designed to redefine commerce experiences through cutting-edge personalization, automation, and operational insights. In this role, you’ll have the unique opportunity to architect and implement scalable ML solutions, lead research projects, and stay ahead of the curve by experimenting with the latest advancements in AI, including LLMs and chatbots.

As a key contributor to our engineering team, you’ll drive the strategy and hands-on implementation of MLOps pipelines, developing and deploying machine learning models that power AI-driven decision-making across our platform. This role is ideal for someone who thrives in ambiguity, loves tackling complex challenges, and is excited to shape the future of AI-powered commerce. You’ll work in a collaborative, fast-paced environment where your ideas will influence the trajectory of both our product and our company. If you’re passionate about building transformative systems and driving impact at scale, we’d love to hear from you.

Responsibilities:

  • Shape FERMÀT's long-term ML/AI strategy and align with the core product roadmap

  • Design, develop, and maintain end-to-end MLOps pipelines, from data ingestion to model deployment and monitoring

  • Provide technical guidance and feedback on ML projects across the organization

  • Experiment with innovative machine learning architectures, incorporating LLMs into traditional ML systems

  • Collaborate closely with Data, Product, and Engineering teams to deploy models into production environments

  • Evaluate and optimize model performance, scalability, and effectiveness, implementing necessary updates

Requirements:

  • 3+ years of experience in traditional machine learning, with exposure to modeling using LLMs

  • 4+ years of professional experience in software engineering

  • Strong proficiency in Python and Javascript, along with other programming languages commonly used in machine learning

  • Expertise in data structures, data modeling, and data visualization, with strong data handling skills

  • Solid background in statistical analysis and data analysis for model training and evaluation

  • Excellent communication skills for collaborating with stakeholders and translating technical concepts

  • Experience in big data processing and feature engineering

  • Previous experience in a fast-paced startup environment

  • Self-motivated with a strong sense of urgency

  • Exceptional problem-solving skills and an aptitude for exploring novel model architectures

  • Bachelor’s or master’s degree in computer science, data science, or a related field

Benefits

  • Competitive salary + equity package

  • Comprehensive health, dental, and vision insurance for you and all your dependents.

  • Retirement benefits:

    • US: 401(k) plan with 4% matching

    • India: Provident Fund with 12% matching

  • 4 months of paid parental leave

  • Unlimited PTO policy (with minimum 5 days PTO / quarter!)

  • WFH stipend

  • Monthly wellness stipend

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Tags: AI strategy Architecture Big Data Chatbots Computer Science Data analysis Data visualization Engineering Feature engineering JavaScript LLMs Machine Learning ML models MLOps Model deployment Model training Pipelines Python Research Statistics

Perks/benefits: Career development Competitive pay Equity / stock options Health care Parental leave Startup environment Unlimited paid time off Wellness

Region: North America
Country: United States

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