Machine Learning Engineer at Pave

San Francisco, California, United States

Apply Now

Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Software, Data TechnologyIndustries

Requirements

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

Responsibilities

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

Skills

Key technologies and capabilities for this role

Machine LearningData ScienceSoftware EngineeringML SystemsData ModelingCollaboration

Questions & Answers

Common questions about this position

What is the salary range for this Machine Learning Engineer position?

This information is not specified in the job description.

Is this Machine Learning Engineer role remote-friendly?

Pave has offices in San Francisco and New York City, is expanding to Salt Lake City, and welcomes remote team members.

What skills are required for the Machine Learning Engineer role?

Candidates need 5+ years building and deploying ML models in production, expertise in Python and ML frameworks like PyTorch or TensorFlow, expert-level SQL skills, experience with MLOps and large-scale data processing, and strong software engineering practices.

What is the company culture like at Pave?

Pave emphasizes playing to win, building with intellectual honesty, focusing on the platinum standard, fast growth, building an incredible team and product, and having fun.

What makes a strong candidate for this Machine Learning Engineer position?

Strong candidates have the ability to navigate ambiguity, bring projects from 0 to 1 or scale from 1 to 100, and Pave encourages applications even if you don't feel entirely qualified.

Pave

Compensation management solutions for businesses

About Pave

Pave provides compensation management solutions designed for businesses of all sizes, particularly those backed by venture capital. Its main product is a suite of tools that integrate with existing HR Information Systems (HRIS), Applicant Tracking Systems (ATS), and Cap Table software, allowing companies to access real-time data for employee compensation planning and benchmarking. This integration helps eliminate the need for spreadsheets and manual data entry, enabling HR leaders to make informed decisions based on accurate information. Pave operates on a subscription-based model, offering various tiers that may include advanced analytics and personalized support. The company aims to simplify the compensation analysis process, making it easier for HR departments to ensure fair and competitive pay, which can lead to improved employee satisfaction and retention.

New York City, New YorkHeadquarters

2019Year Founded

$165.4MTotal Funding

SERIES_CCompany Stage

Data & Analytics, Enterprise SoftwareIndustries

1-10Employees

Benefits

Competitive salary

Equity

Medical, dental & vision coverage

Commuter benefits

Catered lunch

Unlimited PTO policy

Risks

Competition from established HR tech companies like Workday and ADP is intensifying.

Data privacy concerns may arise from integrating with multiple HR systems.

Economic downturns could impact Pave's growth due to reliance on VC-backed clients.

Differentiation

Pave offers real-time compensation data, eliminating the need for spreadsheets.

Seamless integration with HRIS, ATS, and Cap Table systems sets Pave apart.

Pave's platform is powered by the largest real-time compensation dataset globally.

Upsides

Partnership with UKG enhances Pave's platform with valuable organizational data.

Pave's subscription model aligns with growing trends in enterprise software.

Increased focus on pay equity boosts demand for Pave's data-driven solutions.

Land your dream remote job 3x faster with AI

Try Jobo Free