Staff Machine Learning Engineer, Rewards Economy

Mistplay is seeking an innovative Staff Machine Learning Engineer to lead the design and optimization of our rewards economy. In this critical role, you will develop and balance reward systems to ensure they are enticing and add value for our users while maintaining cost-effectiveness for Mistplay. Collaborating with the Data and AI organization, you will lead initiatives in real-time predictive modeling and optimization within our machine learning-driven operations.

What You’ll Do at Mistplay:

• You’ll be part of the cross functional group responsible for the overall rewarding and the loyalty economy strategy for Mistplay.

• Create and implement machine learning driven rewards economy systems and core loops.

• Continuously analyze and optimize the economy strategies and implementations to enhance engagement and drive business outcomes.

• Drive the strategy on how machine learning and AI can further advance the optimization for better user experience and business performance.

• Distill complex model outputs into actionable strategic insights for executive stakeholders, advocating for AI-first approaches to loyalty and retention.

• Design and productionize contextual bandits and RL frameworks to personalize reward distribution in real-time, ensuring the right user gets the right incentive at the right moment.

• Serve as the primary architect for Mistplay’s rewards economy, balancing complex variables to ensure a “win-win” scenario: maximum value for players and sustainable unit economics for the business.

• Partner with Product, Analytics, Engineering, and Finance to translate high-level business goals into algorithmic constraints and incentive structures., At Mistplay, we are very passionate about internal equity, & ensuring all staff members are paid fairly & equally for their position. The final salary offered will vary based on candidate experience & location.

• A combination of 8+ years in Data Science, Machine Learning, Quant, Econometrics, and/or Master’s or Ph.D. in Data Science, Machine Learning, or a related quantitative field.

• Understanding of reinforcement learning (DeepQ, contextual bandits)

• Expertise in implementing machine learning models using Python and PyTorch, paired with strong data analysis skills using SQL and Python.

• Fast and agile approach to exploring and implementing solutions with a strategic focus on the core loop and economy design.

• Experience and background in Quant, Data Science, or related fields, with a foundational understanding of economy and core loop designs in gaming or similar contexts.

• A passion for innovative AI solutions, with demonstrated knowledge in real-time predictive modeling.

• Prior experience in the ad-tech or mobile gaming industry with a focus on the economics of player behavior and engagement strategies is a strong nice-to-have.

We strive to make our work environment as inviting and fun as possible! Working at Mistplay is coupled with a whole array of perks that we’ve adopted virtually and in-person: Team Lunches, game nights, company-wide events, and so much more. Our culture is deeply rooted in growth and upheld by a team of smart, dynamic, and enthusiastic people. We utilize data to constantly learn, improve, and adapt. We foster an environment where everyone is encouraged to share their ideas, push boundaries, take calculated risks, and witness their visions come to life.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

The salary listed is based on the National Average across the US, & based on base salary only, there is a bonus component & many additional benefits, including equity.

For candidates who demonstrate full readiness for the defined scope of the role, the typical starting salary is $190,000 USD. Offers below this point reflect candidates we believe can grow into the full scope of the role with support and development. Offers above this point reflect impact that meaningfully exceeds the role’s defined expectations or an expanded scope from day one.