Machine Learning Engineer
Remote • San Francisco • FullTime
Posted 2mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Machine Learning Engineer
About the job
HappyRobot is building the infrastructure for enterprises to create and manage AI workforces that can make decisions, take action, and run operations autonomously across enterprise systems. We are a well-funded startup (over $200M raised) backed by top investors like a16z and Y Combinator, powering critical operations for global enterprises. This role offers a unique opportunity to be one of our first Machine Learning hires, significantly impacting our technology and company direction. You will be responsible for the entire lifecycle of ML systems, from design to production deployment, ensuring we remain at the forefront of AI innovation.
Responsibilities
- Design, build, and maintain scalable ML systems, including data ingestion, preprocessing, training, testing, and deployment.
- Develop and optimize end-to-end ML pipelines for data collection, labeling, training, validation, and monitoring.
- Implement MLOps practices such as model versioning, experiment tracking, CI/CD for ML, and continuous production monitoring.
- Collaborate with product and engineering teams to integrate and deploy models into real-time products, focusing on efficiency and scalability.
- Ensure data quality, observability, and performance across all AI systems.
- Stay current with the latest AI infrastructure, tooling, and research to maintain a competitive edge.
Requirements
- Strong experience in machine learning, deep learning, and NLP.
- Solid background in MLOps and data pipelines, including model deployment, monitoring, and scaling in production.
- Proficiency in Python and familiarity with Go.
- Experience with ML lifecycle management tools (e.g., MLflow, Kubeflow, Weights & Biases).
- Ability to design robust, scalable, and automated ML systems.
- Strong coding, debugging, and data engineering skills.
- Passion for AI infrastructure and its real-world impact.
- Founder mindset with ownership, independence, and a willingness to dive deep.
Benefits
- Comprehensive benefits including healthcare, dental, and vision coverage.
- Competitive salary and equity in a high-growth startup.