Machine Learning Engineer

Position Overview: 

Do you enjoy working on data-intensive products and being involved in projects from an early stage?  Come join our quickly growing Engineering team to help design, improve and scale OfferFit's self-learning (reinforcement learning) AI platform.

In particular, you will:

• Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge ML product.
• Work closely with customer-facing teams to understand, translate, and generalize particular use cases to generic platform components.
• Apply your extensive knowledge of Python and its ecosystem to produce clean, readable, and extendible code, and coach others on the team in doing the same.
• Collaborate with teams responsible for OfferFit’s product strategy and roadmap.
• Support teams implementing OfferFit for customers to ensure their success.
• Work closely with our Applied Science team (data scientists) to help productize and deploy attribution and reinforcement learning algorithm improvements
• Improve our core data pipelines and reporting architecture.

Tech stack:

• Data Science/Back End: Python (Pandas, Polars, Ibis, Spark), SQL, BigQuery, FastAPI
• Web [Not required for this role]: JavaScript (Vue, Node.js), HTML, CSS
• Architecture/DevOps: Kubernetes, Airflow, Terraform, GCP
• We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development.

Why is it great: 

No toy datasets in notebooks — we’re implementing AI pipelines in production at scale!

1. Learn tons about data architecture, data science, and self-learning AI.
2. Work in a team that not only talks the talk of development best practices, but walks the walk — unit & integration tests, modular design, CI/CD, pair programming, code reviews — the works.
3. Join OfferFit’s fast-paced, supportive, and professional team. We make sure all of our team members are empowered and receive great mentorship and coaching.

Who’s a Fit: 

• Exceptional coder: you write clean, object-oriented code; you care about good design and terse, testable APIs.
• Tinkerer: you regularly explore and learn new technologies and methods, especially in the data architecture and data science domains.
• Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes.
• Structured and organized: you can structure a plan, align stakeholders, and see it through to execution.
• Clear communicator: you are able to express yourself clearly and persuasively, both in writing and speech.
• Background in Machine Learning Engineering and/or Data Engineering is preferred. Some Data Science experience is nice-to-have but is not required.

Ideal Skills and Experience: 

• 2+ years of experience working with Python in a production setting, including 1+ years in the data / machine learning ecosystem
• Experience working with at least one major cloud platform (GCP, AWS, Azure, etc.)
• Experience putting ML models into production
• General understanding of supervised learning principles is a plus but not required

OfferFit Benefits and Perks:

• Generous PTO (starting at 25 days PTO per year) and Parental leave policy (12 weeks paid)
• 100% remote work environment with flexible hours 
• Quarterly gatherings where we meet in person in a different city to work together, bond as a team and celebrate our progress
• Weekly team events (lunch and learns, trivia, virtual escape rooms, town hall and team health “barometer” meetings)
• Ability to learn and develop from an experienced leadership team (ex-Amazon, McKinsey, BCG, and IBM, among others) who are focused on building a talented, diverse, and inclusive team
• Dedication to building a strong culture (e.g., team resource groups, weekly recognitions, major life event celebrations, mental health/sustainability days off, etc.)

Additional Requirements:

• Fluency in English is required for this position 
• Ability to partially overlap with US time zones required 

Please note that we adjust compensation for non–US countries using a relative cost of labor adjustment between the US and your country of residence.  Applicants should apply via OfferFit’s internal or external careers site.