Senior Machine Learning Engineer

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.

• 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.

Compensation:

• Negotiable base salary + annual bonus