Machine Learning Scientist

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.

• 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.

• 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.

• 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.