Ibotta is looking for a Staff Machine Learning Engineer to join our machine learning team. As our next Staff Engineer you will be building our recommender systems and multi-armed bandit models. You will be working cross functionally across our technical organization to drive innovative solutions around personalized recommendations and item rankings across all our product offerings including mobile, browser extension, and more. Your work will be directly reflected in Ibotta’s user engagement, redemption levels, and revenue.
This position is located in Denver, Colorado or with the option of full-time remote. Candidates must live in the United States.
What you will be doing:
- Embrace and uphold Ibotta’s Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency & Advocate for Savers
- Work cross functionally with product management, engineering, and analytics to lead projects of various scope and size
- Serve as technical expert on the team responsible for designing, developing and deploying large scale, big data-driven recommendation and personalization models that are integrated across the Ibotta ecosystem
- Understand the broader architecture and how its evolving short to medium term
- Own testing, reliability and performance plan for team initiatives. Work with stakeholders from other teams on final acceptance testing to ensure show-ready delivery.
- Understand trade-offs and priorities to align on a solution that balances the needs across teams
- 6+ years of experience as machine learning engineer or applied machine learning scientist
- Previous experience of technical leadership
- Expert in Recommender Systems, Machine Learning and more
- Proven expertise with data handling, processing, statistical and analytical skills
- Ability to think creatively and provide thoughtful, agile insights
- Python expert and experience using modern data analysis tools (such as TensorFlow, PyTorch) and familiarity with Apache Spark is required
- Knowledge of cloud services (AWS preferred)
- Ability to develop and maintain ML models
- Ability to visualize, analyze, and communicate results
- Good understanding of A/B testing
- Ability to lead and work collaboratively to drive towards common goals
Built in Denver, CO, Ibotta ("I bought a...") is a free mobile shopping app that gives users cash back on groceries and more. Through our partnerships with brands and retailers like Procter & Gamble, Kraft Heinz, Kellogg, Amazon, Walmart, Target and Uber, we’ve delivered over $800 million in cumulative cash rewards to our Savers. Guided by our values and our mission to make every purchase rewarding, we come to work energized by the business problems we get to solve, the technology we get to build, and the people we get to innovate (and have fun) with. Ibotta made Inc.’s 2020 list of the 5000 fastest-growing private companies in the U.S. for the third consecutive year. In 2019, we became the first mobile consumer technology company in Colorado to achieve $1B in valuation.
To learn more about what our Tech teams are doing day to day, visit Building Ibotta on Medium.com
- This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Lifestyle Spending Account, 401k match, profit sharing and equity.
- Base compensation range: $150,000-$175,000. Total compensation for this role also includes a variable component in addition to base salary.
- Ibotta is an Equal Opportunity Employer. Ibotta’s employment decisions are made without regard with race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected status.
- Applicants must be currently authorized to work in the United States on a full-time basis.
- For the security of our employees and the business, all employees are responsible for the secure handling of data in accordance with our security policies, identifying and reporting phishing attempts, as well as reporting security incidents to the proper channels.