Machine Learning Applied Scientist

Job description

OfferFit was founded by ex-McKinsey and BCG math PhDs, and we’re funded by leading Silicon Valley VCs. OfferFit’s AI decisioning engine supports 1:1 personalization for lifecycle marketing campaigns, powered by reinforcement learning AI. This allows marketers to test & improve the performance of their campaigns much faster than before. Customers include leading brands like Brinks Home, Yelp, Chime, Engie, and MetLife, among many others.

Note for Applicants:

Data shows that men on average apply for a role if they meet ⁶⁄₁₀ requirements while women often only do so if it’s ¹⁰⁄₁₀.  We work hard to be clear and specific about what our roles require, and we encourage you to apply even if you don’t check all the boxes!  Applying gives you the opportunity to be considered and we look forward to reviewing your application!

Our team is growing! We’re looking for an RL researcher or practitioner who will apply reinforcement learning to solve real-world customer communication challenges.  In this role, you’ll work closely with the CTO and Engineering team to improve sample efficiency, test credit assignment and attribution algorithms, investigate and improve our approach to action space featurization, reward shaping, combining RL with constrained optimization, and other interesting challenges. Currently, we use ensembles of contextual bandits to achieve high sample efficiency and coordination of decisions, and we’re constantly testing and implementing improvements.

Your responsibilities will include:

• Improve RL algorithms to increase performance, sample efficiency, and robustness at scale
• Develop and apply advanced diagnostic tools, including off-policy evaluation methods
• Conduct research on state-of-the-art RL techniques and their applicability to marketing optimization
• Implement better monitoring and observability tooling
• Work closely with engineering teams to improve OfferFit’s platform and develop APIs for OfferFit ML components
• Participate in customer implementations to gain insights into real-world use cases
• Contribute to OfferFit’s product strategy and roadmap

Tech stack:

• Data Science/Back End: Python ML ecosystem, Spark, BigQuery, FastAPI
• Architecture/DevOps: Kubernetes, Airflow, Terraform, GCP
• Web [not required for this role] : TypeScript, JavaScript, Vue.js and its ecosystem, Node.js, Strapi, PostgreSQL, HTML5, CSS3
• 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 generating real value.

1. Opportunity to bridge cutting-edge RL research with real-world applications.
2. Access to large-scale datasets and computational resources.
3. Support for continued research, including conference attendance and publication.
4. Collaboration with a diverse team of experts in ML, engineering, and marketing.
5. 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 have experience on writing clean, well-designed, versioned code; you care about good coding practices and terse, testable APIs.
• Problem solver: you thrive on tackling complex, real-world challenges with novel ML approaches
• Impact-driven: you’re motivated by seeing your research translate into tangible business outcomes
• Collaborative: You enjoy working closely with a team of driven individuals across multiple teams to get things done. You’re willing to both help and ask for help.
• 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.
• Ph.D. in Computer Science, Machine Learning, or a related field with a focus on Reinforcement Learning. MS with professional experience with RL is fine too.

Additional Requirements:

• Candidates must be able to partially overlap and support North America time zones
• Must be fluent in English, both written and verbal
• Up to10-15% travel for company-wide quarterly gatherings, team offsite workshops, customer meetings, and industry-related events

The base salary range for this position in the United States is $120,000-$180,000 per year, plus eligibility for additional bonus ranging $15,000-$22,000; Eligibility for an additional end of year performance bonus, commissions (when applicable) and/or equity options may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, depending on the position offered.  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.

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.)
• [US Only] Competitive benefits (major medical, vision, dental and LTD) and 401K matching program

OfferFit is committed to a diverse and inclusive workplace. OfferFit is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.