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Machine Learning Engineer
Machine Learning EngineerTrov • San Francisco, CA, United States
Machine Learning Engineer

Machine Learning Engineer

Trov • San Francisco, CA, United States
15 days ago
Job type
  • Full-time
Job description

At Pave, we’re building the industry’s leading compensation platform, combining the world's largest real-time compensation dataset with deep expertise in AI and machine learning. Our platform is perfecting the art and science of pay to give 8,500+ companies unparalleled confidence in every compensation decision.

Top tier companies like OpenAI, McDonald’s, Instacart, Atlassian, Synopsys, Stripe, Databricks, and Waymo use Pave, transforming every pay decision into a competitive advantage. $190+ billion in total compensation spend is managed in our workflows, and 58% of Forbes AI 50 use Pave to benchmark compensation.

The future of pay is real-time & predictive, and we’re making it happen right now. We’ve raised $160M in funding from leading investors like Andreessen Horowitz, Index Ventures, Y Combinator, Bessemer Venture Partners, and Craft Ventures.

Research & Design Org

Pave's R&D pillar includes our data science, engineering, information technology, product design, product management, and security teams. This organization builds, maintains, and secures a platform used by more than 8,500+ client organizations.

Our engineering team moves between ideation, scoping, and execution in a matter of days while closely iterating with cross‑functional partners on requirements. At Pave, we use TypeScript, Node.js, and React, hosted on GCP. Compensation strategy is broken down into three pillars – compensation bands , planning workflows , and total rewards communication . We build products that make these processes seamless for customers.

Over the next year, our roadmap is focused on enhancing the entire compensation lifecycle : from philosophy definition to market trend analysis, band adjustments, merit cycles, and employee communication. We’re seeking passionate engineers who are excited about building robust, data‑rich systems that simplify complex compensation processes at scale.

The Data Team @ Pave

As part of the Data team at Pave, you will help us redefine how companies understand the labor market and determine compensation. Even the most innovative tech companies in the world often use spreadsheets full of flawed statistics to determine how to pay. At Pave, we’ve built a system of real‑time integrations that allow us to bring best practices from machine learning, data science, software tooling, and AI to an industry that is built on data, but doesn’t have the tools it needs to fully leverage it.

What You’ll Do

  • Architect and implement scalable ML systems for modeling compensation within a single company and across the market as a whole
  • Collaborate with product and engineering teams to identify additional opportunities to leverage ML‑driven solutions
  • Help evolve the technical direction of ML initiatives across the company
  • Drive millions of dollars of revenue growth

What You’ll Bring

  • 5+ years of experience building and deploying ML models in production environments
  • Strong foundation in machine learning, statistics, and deep learning fundamentals
  • Expertise in Python and modern ML frameworks (PyTorch, TensorFlow, or similar)
  • Experience with large‑scale data processing and ML model optimization
  • Experience with MLOps practices and tools (model versioning, monitoring, and deployment)
  • Strong software engineering practices and experience with production systems
  • Expert‑level SQL skills with experience writing complex queries and optimizing query performance
  • Ability to navigate (and bring structure to) ambiguity; ability to bring a project from 0 to 1, or scale a project from 1 to 100
  • Compensation

    Salary is just one component of Pave’s total compensation package for employees. Your total rewards package at Pave will include equity, top‑notch medical, dental, and vision coverage, a flexible PTO policy, and many other region‑specific benefits. Your level is based on our assessment of your interview performance and experience, which you can always ask the hiring manager about to understand in more detail. This salary range may include multiple levels.

    The targeted cash compensation for this position is (level depends on experience and performance in the interview process) :

    P3 : $195,000 – $215,000

    P4 : $230,000 – $250,000

    Life @ Pave

    Since being founded in 2019, Pave has established a robust global footprint. Headquartered in San Francisco’s Financial District, we operate strategic regional hubs across New York City’s Flatiron District, Salt Lake City, and the United Kingdom. We cultivate a vibrant, collaborative workplace culture through our hybrid model, bringing teams together in‑person on Mondays, Tuesdays, Thursdays, and Fridays to foster innovation and strengthen professional relationships.

    Benefits

  • Complete Health Coverage : Comprehensive Medical, Dental and Vision coverage for you and your family, with plenty of options to suit your needs
  • Time off & Flexibility : Flexible PTO and the ability to work from anywhere in the world for a month
  • Meals & Snacks : Lunch & dinner stipends as well as fully stocked kitchens to fuel you
  • Professional Development : Quarterly education stipend to continuously grow
  • Family Support : Robust parental leave to bond with your new family
  • Commuter Assistance : A commuter stipend to help you collaborate in person
  • Vision & Mission

    Our vision is to unlock a labor market built on trust.

    Our mission is to build confidence in every compensation decision.

    Equal Employment Opportunity

    As set forth in Pave’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. If you believe you belong to any of the categories of protected veterans listed below, we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA.

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