Remote Staff Machine Learning Engineer

Summary

Join our Data, Systems & Intelligence (DSI) team as a Staff Machine Learning Engineer to help internal Sales and Customer Success clients through the delivery of scalable AI/ML and other data products. You will work collaboratively with ML Engineers, ML Ops team, GTM Data Platform team, Flywheel Product team, and many other teams.

Requirements

• Degree in computer science, statistics, applied mathematics, economics, or other quantitative discipline
• 5+ years experience in machine learning with multiple models deployed in operational settings
• Expert knowledge of a breadth of machine learning/AI techniques and a thorough understanding of the best approach to use for a given situation
• Expert knowledge of Python programming and ML frameworks (Scikit-learn, TensorFlow, PyTorch, HuggingFace, etc.)
• Extensive familiarity with CI/CD systems (e.g. GitHub Actions, Jenkins, CircleCI, etc.)
• Familiarity with monitoring & alerting systems (DataDog, Monte Carlo, Cloudwatch)
• Familiarity with Snowflake, SQL, as well as DBT and jinja templating
• Familiarity with standard ML deployment stack (Docker, Kubernetes, Spark, dask, etc.)
• Ability to own a software project from planning to maintenance. Agile or scrum familiarity preferred. Works well with backend/frontend/full stack engineers
• Proven track record of delivering high-impact ML/AI products
• Able to clearly communicate highly technical concepts to business leaders in both slides and memos
• Creative, collaborative problem solver with experience delivering iterative solutions to difficult problems

Responsibilities

• Build, train, evaluate, and deploy ML models and generative AI (GAI) solutions at scale, both batch and near real time
• Query, integrate, analyze, and preprocess rich and complex datasets (both structured and unstructured) to extract relevant features and insights
• Conduct experiments and evaluations of ML and generative AI models, using statistical methods and visualization tools to assess performance and identify areas for improvement
• Train and fine-tune LLMs for specific, tailored use cases
• Build strong relationships with internal stakeholders and develop a deep understanding of their business problems
• Keep current with the research and trends in AI/ML/GAI, and contribute to the development of new algorithms and techniques
• Participate in code reviews, testing, and documentation activities, ensuring high quality and maintainability of the codebase
• Mentor other junior ML Engineers and Data Scientists to improve their coding proficiency, algorithmic efficiency and general knowledge of the rapidly evolving field

Benefits

Cash compensation range: 218900-328400 USD Annually