Staff Machine Learning Engineerto join our Core Data & Analytics team and contribute to our mission to Make Every Purchase Rewarding. We're looking for someone who has a passion for building scalable machine learning solutions using technologies and tools such as Python, Spark, Databricks, AWS, Sagemaker, etc. As a Staff Machine Learning Engineer, you will act as a technical leader and delivery owner for complex, high-impact ML initiatives spanning foundation models, data systems, and large-scale ML platforms. This role will immediately impact ML strategy and drive impact through the support, guidance, and collaboration with multiple teams as part of our analytics organization. We're looking for a technical leader to further mature our current infrastructure and abstractions and identify new opportunities to add value through ML applications.

This position is available in multiple locations:

Denver, Colorado - if you are in or willing to relocate to the Denver area, this is a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday).

Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NY, NC, OH, OK, PA, TN, TX, UT, VA, WA, WI. Not based in one of these areas? We will offer a relocation bonus to help make your move to the Mile High City a smooth one.

What you will be doing:

• Lead the design, development, and deployment of production-grade ML systems across the organization.
• Work with Ibotta architecture and Machine Learning Platform teams to ensure integration of machine learning services and pipelines in larger technology infrastructure.
• Act as a liaison between technical teams and non-technical stakeholders to communicate complex concepts clearly.
• Communicate complex machine learning solutions, concepts and the results of analyses in a clear and effective manner to business stakeholders and technology leaders to maximize the effectiveness of machine learning initiatives.
• Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous experimentation, and best practices.
• Embrace and uphold Ibotta's Core Values: Integrity, Boldness, Ownership, Teamwork, Transparency & A good idea can come from anywhere

What we are looking for:

• 6+ years of professional industry experience as a Machine Learning Engineer or Software Engineer, focused on deploying machine learning systems at scale.
• Advanced knowledge of multiple ML frameworks like: Sklearn, TensorFlow, Sagemaker, Spark ML.
• Expertise working with distributed big-data tools and event-based architectures, ideally Spark and Kafka.
• Deep hands-on experience prototyping, building, releasing, and monitoring mission-critical machine learning models in high traffic applications.
• Experience working within a cloud-based infrastructure, ideally AWS.
• Track record of mentoring junior engineers or leading cross-functional initiatives.

Additional Details:

• This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Lifestyle Spending Account, Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, snacks, and occasional meals.
• Base compensation range: $206,000 - $230,000 Equity is included in overall compensation package. This compensation range is specific to the United States labor market and may be adjusted based on actual experience.
• Applicants must be currently authorized to work in the United States on a full-time basis.
• Applicants are accepted until the position is filled.
• 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.

Recruiting Agency Notice
Ibotta does not accept agency resumes and is not responsible for any fees related to unsolicited resumes. Please do not forward resumes to any Ibotta employees.

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