Machine Learning Scientist at Scopely

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Feb, 26

Salary

185000.0

Posted On

09 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, PyTorch, TensorFlow, Scikit-learn, Data Science, Data Engineering, A/B Testing, Model Evaluation, Geospatial Data, Problem Solving, Communication, Collaboration, Real-time Decision Making, Cloud Computing, Geo-contextual Modeling

Industry

Entertainment Providers

Description

Niantic’s Machine Learning Team seeks a Machine Learning Scientist to join our AI/ML team. This role focuses on crafting and implementing machine learning-powered features for our geo-location-based mobile games. You will collaborate closely with product managers, game designers, engineers, and data scientists to craft intelligent game mechanics that respond to player behavior, contextual environments, and geospatial signals. This is a high-impact, hands-on role ideal for candidates passionate about applying ML to mobile games and real-world data challenges. Niantic is a leading mobile game developer known for groundbreaking real-world mobile gaming experiences. Our mission is to use new technologies to enrich the human experience and encourage exploration of the world around us. Titles like Pokémon GO, Pikmin Bloom, and Monster Hunter Now are just the beginning. We’re looking for curious, creative, and purposeful minds to join us on our journey. Responsibilities Craft and develop machine learning models that drive intelligent gameplay features, such as multifaceted content placement, player clustering, and geo-contextual personalization. Leverage real-world data (geospatial, temporal, behavioral) to advise in-game decision-making and adapt to player environments in real time. Partner with product and design teams to translate gameplay ideas into ML-powered systems. Collaborate with data science and data engineering teams to optimize data pipelines for machine learning use cases. Collaborate with product and data science teams to perform thorough experimentation, A/B testing, and model evaluation to measure product impact and feature efficiency. Contribute to the design of ML infrastructure, tools, and workflows that support the lifecycle of models in production. Required in-office 2 days on Tuesday and Wednesday. Qualifications M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or related technical field. 2+ years of experience developing ML systems in a production environment. Proficiency in Python and ML libraries such as PyTorch, TensorFlow, Scikit-learn, or similar. Experience with applied ML techniques such as supervised learning, clustering, or deep learning. Strong analytical and problem-solving skills with a product mentality. Ability to communicate technical concepts clearly to multi-functional teams. Ability to work in a fast-paced hybrid environment and handle stress appropriately and/or ability to solve practical problems and be sufficiently adaptable to handle dynamic situations with little advance notice. Experience working on cross-functional teams with ability to communicate effectively through written and verbal communications, including asynchronous interactions with others. Plus If... Experience building ML features for mobile games or interactive applications. Experience with modern data processing frameworks, e.g. Apache Beam or Apache Spark. Exposure to active learning methodologies, recommendation systems and real-time model inference. Experience with Cloud native model development environments, e.g. GCP or AWS. Experience with common machine learning development tools or frameworks, e.g. Jupyter Notebooks, MLflow or Kubeflow. Familiarity with geo-contextual modeling, map-based data, and temporal-spatial modeling techniques. Solid understanding of geospatial data and location-based modeling challenges. For candidates in CA, CO, NJ, NY, and WA, the annual salary range is provided below. In addition to base pay, employees may be eligible for equity, bonuses, and a comprehensive benefits package, including healthcare benefits, retirement benefits, pet insurance, paid holidays, paid Scopely free days, and unlimited paid time off. Base pay offered may vary depending on job-related knowledge, skills, and experience. CA, CO, NJ, NY, and WA Annual Salary Range $158,200—$185,000 USD About Us Scopely is a global interactive entertainment and mobile-first video game company, home to many top, award-winning experiences such as "MONOPOLY GO!," “Star Trek™ Fleet Command,” “Stumble Guys,” “MARVEL Strike Force,” and “Yahtzee® With Buddies,” among others. Scopely creates, publishes, and live-operates immersive games that empower a directed-by-consumer™ experience across multiple platforms--from mobile, web, PC and beyond. Founded in 2011, Scopely is fueled by a world-class team and a proprietary technology platform Playgami that supports one of the most diversified portfolios in the games industry. Recognized multiple times as one of Fast Company’s “World’s Most Innovative Companies,” Scopely is a multi-billion-dollar business due to its ability to create long-lasting game experiences that players enjoy for years. Scopely has global operations in more than a dozen markets across Asia, EMEA, and North America, and is home to many internal game development teams, referred to as Scopely Studios, with additional game studio partners across four continents. Scopely was acquired by Savvy Games Group in July 2023 for $4.9 billion, and is now an independent subsidiary of Savvy. For more information on Scopely, visit: scopely.com Notice to candidates: Scopely, Inc and its affiliates will never request payment or ask for financial information as a condition for applying to a position or receiving an offer of employment. All official Scopely, Inc. recruiters only use email domains that end with @scopely.com. Our official website is www.scopely.com. Please only apply to positions posted on our official website and ensure the recruiter only communicates via the official email domain. Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here: California Privacy Notice and EEA/UK Privacy Notice. Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.

Responsibilities

Craft and develop machine learning models that drive intelligent gameplay features and leverage real-world data to adapt to player environments in real time. Collaborate with product and design teams to translate gameplay ideas into ML-powered systems.