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BuildOps

Senior Machine Learning Engineer

Reposted 13 Hours Ago
Easy Apply
Hybrid
Los Angeles, CA
Mid level
Easy Apply
Hybrid
Los Angeles, CA
Mid level
Implement and enhance AI/ML features in our platform, build and deploy machine learning models, and collaborate with multiple teams to deliver software solutions.
The summary above was generated by AI

At BuildOps, we’re building a groundbreaking software solution designed to support today’s commercial contractors. From managing service departments to project management, we’re breaking the mold and building a team that’s invested in our mission. We thrive on hiring driven, self-motivated individuals with tech start-up experience who excel in fast-paced environments. Could you be our next hire?

This role offers the opportunity to join a well-funded, fast-growing technology startup and help build out a critical function for the company.

As a Senior Machine Learning Engineer, your primary focus will be implementing and enhancing AI/ML features in our industry-leading platform. We’re looking for someone who is passionate about delivering practical, high-quality software and can collaborate effectively in a distributed team environment.

What You'll Do:

  • Build and deploy machine learning models using Python (e.g., PyTorch) on platforms like AWS SageMaker
  • Develop backend and client-side code to integrate with cloud-based LLM APIs (e.g., Bedrock, ChatGPT APIs).
  • Manage monitoring (Wandb.ai, MLFlow, etc), deployment, and assist with hyperparameter tuning
  • Implement your own ML endpoints in our various React/NodeJS applications
  • Collaborate with data scientists and cross-functional teams to deliver impactful and practical AI solutions
  • Work in tandem with the quality engineering team to ship high-availability software
  • Build and maintain automated unit tests: unit, integration and UI
  • Participate in PR reviews and ensure proper implementation of ML tooling across our stack
  • Communicate effectively with engineers, product managers, customers, partners, and other leaders.
  • Stay up-to-date on the latest AI technologies and trends to help other areas of the company find leverage in new advancements

What We Look For:

  • 2+ years of experience in developing AI solutions preferably with LLMs
  • 5+ years of experience in Full Stack software development 
  • 5+ years of experience in Python
  • 3+ years of experience in Javascript/Typescript, Node.js
  • Familiar with MLOps/deployment best practices (Sagemaker experience is a plus)
  • Familiarity with vector databases and text embeddings
  • Proven ability to manage/deploy machine learning models
  • Experience with AI/ML frameworks such as TensorFlow, PyTorch, numpy or scikit-learn
  • Strong communication and technical writing skills.
  • Familiarity with unit testing, debugging, profiling and performance monitoring in AWS environment.
  • Prior experience with Node.js, building features using REST and/or GraphQL APIs using Apollo preferred
  • Prior knowledge or ability to quickly learn developing in a MLOps environment (MLflow or similar) preferred.
  • Ability to work a hybrid schedule - Monday/Friday WFH, Tuesday - Thursday, in office.

What We Offer:

  • Negotiable base salary + annual bonus
  • Generous equity grant, become an owner in our company!
  • A comprehensive benefits package
  • Flexible PTO and hybrid work schedules
  • Work from home stipend
  • Hubs in Los Angeles, Toronto, and Raleigh with hybrid work schedules with lunch provided for in-office days
  • Company events like BBQs and team-building activities, both in-person and virtual
  • Fast-paced, collaborative, and dynamic work environment
  • Opportunities for growth and career advancement
  • Chance to work with cutting-edge technology and innovative solutions
  • The chance to get in on the ground floor and build something truly groundbreaking for ourselves and our amazing customers

About BuildOps:

BuildOps is a fast-paced, high-growth start-up committed to transforming a $300B+ industry through an innovative all-in-one SaaS platform. Leveraging the latest technology, we’re taking Commercial Specialty Contractors from the world of pen and paper to cloud-based, data-driven operations. Our leadership team has deep experience in both the Construction and SaaS technology industries, as well as a resume that includes Stanford, Harvard, Wharton, Cornell, Microsoft, and multiple successful start-up exits.

BuildOps has more than doubled year-over-year while raising over $140 million in total funding (including a recent round in Feb 2024). Top-tier investors like Founders Fund, Siemens, B Capital Group (BCG's venture arm), 01 Advisors, and more have backed BuildOps! Also, Dick Costolo, former CEO of Twitter, just joined our board, adding to an impressive group of investors/advisors including former President of Salesforce, Gavin Patterson; CAA founder Michael Ovitz; NFL legend Joe Montana; former heavyweight champion Mike Tyson, and Boost Mobile CEO Stephen Stokols.

Forbes Magazine
“BuildOps is unique because it addresses the problem of efficiency in construction for an often-overlooked audience. Rather than focusing on large projects, or catering to owners, they look to the needs of technician-heavy subcontracting firms working in the commercial space.”

TechCrunch
“The new financing will be used to support the company’s continued growth. BuildOps sells software that integrates scheduling, dispatching, inventory management, contracts, workflow and accounting into a single software package for commercial real estate contractors with staff ranging from a few dozen to several hundred employees.”

Crunchbase
In a statement, [former NFL superstar] Joe Montana noted that his firm (Liquid 2 Ventures) has an investment thesis in supporting America’s working class… “I just love the idea of making their lives far easier and better,” he said. With BuildOps, “you have one solution that does it all and talks seamlessly to every single part of their business from parts to ordering to inventory and more.”

Top Skills

Apollo
Aws Sagemaker
GraphQL
JavaScript
Mlflow
Node.js
Python
PyTorch
React
Rest
TensorFlow
Wandb.Ai

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