Senior Machine Learning Engineer

 Senior Machine Learning Engineer
Location: Hybrid in San Francisco, Los Angeles, New York, Menlo Park, or Toronto
Type: Full-time
Compensation: $190K–$245K + competitive equity
Visa Sponsorship: Not available
Work Policy: Hybrid (2 days/week in office)

About the Company
This is a well-funded, product-led company applying AI to solve a painful and often-overlooked challenge in professional services. The product is already live with enterprise clients and backed by over $150M in funding. The team is scaling rapidly and hiring senior ICs who want to make measurable impact in a production environment.

You’ll join a high-caliber, low-ego team with deep technical and product experience. Engineering has a seat at the table, and the ML team is critical to the company’s next stage of growth.

The Role
As a Senior Machine Learning Engineer, you’ll own end-to-end model development—from prototyping to production deployment. You’ll work directly on core product features that affect thousands of users and integrate ML into the heart of the company’s customer experience. This is a senior IC role with high visibility and high impact.

What You’ll Do

• Tackle real product challenges. Translate messy, ambiguous problems into ML systems that deliver real business value.

• Build and deploy full ML pipelines. Own everything from data preparation to model serving and monitoring.

• Mentor and elevate others. Bring technical leadership, guide best practices, and help the team scale with quality.

• Balance rigor and pragmatism. Break ambitious ideas into testable pieces. Ship quickly, learn constantly.

• Work across teams. Collaborate with product, design, and infrastructure to make sure your models drive user and business outcomes.

What We’re Looking For

• 5+ years of experience in ML/AI engineering roles, ideally in both startup and large-scale environments

• Strong Python skills and deep experience with PyTorch or TensorFlow

• Proven track record shipping ML systems into production, not just prototypes

• Comfortable working with large-scale data and MLOps tools

• Familiar with LLMs, prompt engineering, and dataset curation

• Experience in at least one of: NLP, ranking models, classification, or computer vision

• Holds or held a senior title in a technical team; MS/PhD or research experience is a plus

Nice to Have

• Built ML infra or worked on real-time inference systems

• Mixed experience across Series B–D startups and Big Tech

• Demonstrated long-term impact in past roles

Tech Stack
Python, PyTorch, TensorFlow, SQL, AWS, Azure, Airflow, MLFlow, Docker, Postgres, Vector DBs, Terraform

Interview Process

1. Intro & Screening (15–30 mins)

2. Technical Coding Interview (1 hour)

3. Panel Rounds (ML System Design, Programming, Culture, General System Design)