Phia

Technology

SeniorMachineLearningEngineer

$185–265k New York, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning Engineer at Phia. Skills: Machine learning, MLOps, Data engineering. Design production ML models. Develop production ML models”

Industry & Context.

Technology

What They're Looking For.

Must Have

3+ years industry experience, Python proficiency, ML frameworks experience, Full ML lifecycle experience, Large-scale datasets experience, Experiment design understanding, Causal inference understanding, Cross-functional collaboration, Clear technical communication, Bachelor's degree or equivalent

Nice to Have

PhD preferred

What You'll Do.

Design production ML models

Develop production ML models

Deploy production ML models

Partner with Engineering

Partner with Operations

Translate requirements

Translate business goals

Develop experimentation frameworks

Develop causal measurement strategies

Build forecasting systems

Build ranking systems

Build personalization systems

Build optimization systems

Improve model performance

Improve model reliability

Improve model scalability

Contribute to ML platform

Contribute to ML infrastructure

Influence technical direction

Conduct design reviews

How You'll Work.

Team & Collaboration

Cross-functional partners

Communication Scope

Technical concepts clarity

Full Job Description

OVERVIEW As a Senior Machine Learning Engineer at Phia, you’ll build and scale production ML systems that power core product experiences and decision-making. You’ll work across the full ML stack, from data and modeling to deployment and iteration, on problems like ranking, personalization, and optimization. This role sits at the intersection of machine learning, product engineering, and data platforms, with ownership over systems that directly impact growth and user experience. You’ll ship models to production, run experiments at speed, and help define how machine learning is done as Phia scales. ABOUT PHIA Phia has raised $43M from Notable Capital, Khosla Ventures, and Kleiner Perkins, with backing from founders and operators like Vlad Tenev (Robinhood), Mellody Hobson (Ariel Investments), Naomi Gleit (Meta), and Mati Staniszewski (ElevenLabs), plus a roster of cultural leaders, to build the AI alignment layer for commerce. In just over a year, Phia's consumer shopping agent has surpassed 1.5 million users and partnered with 9,600+ retail brands across contemporary, resale, and luxury, representing billions in annual gross merchandise volume. We scan more than 350 million products to help shoppers find the right pieces at the best price, cutting return rates by 50%, and we're on pace for nine-figure sales growth this year.   In an era where AI vertical agents are reshaping every industry, commerce is on the verge of a complete transformation. Phia is reinventing shopping from a fragmented, impersonal experience into one that feels intelligent, trusted, and built around each user's intent. This foundation of trust is our wedge to become the end-to-end shopping destination for the next generation of buyers.   Phia is a lean, high-ownership team building at startup speed. If you want to ship at high velocity and solve complex problems in consumer AI and commerce, this is the place to do it. WHAT YOU OWN - Design, develop, and deploy production machine learning models

Free ATS check

Applying for this Senior Machine Learning Engineer role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Ashby

  • Ashby is a fast modern ATS — most applications take under 3 minutes.
  • The resume parser is strong; verify parsed experience dates and job titles.
  • Custom screening questions are often scored algorithmically — answer completely.
  • Location field affects geo-based screening; use your actual metro area.

ANONYMOUS · UNFILTERED

What do employees actually say about Phia?

Real rants from real employees. Read before you apply.

Read Company Rants →