Machine Learning Scientist

1 Month ago • 2 Years + • Research Development • $158,200 PA - $185,000 PA

Job Summary

Job Description

Niantic's Machine Learning Team is looking for a Machine Learning Scientist to develop and implement machine learning-powered features for their geo-location-based mobile games. The role involves collaborating with product managers, game designers, engineers, and data scientists to create intelligent game mechanics that respond to player behavior, contextual environments, and geospatial signals. This is a high-impact position for individuals passionate about applying ML to mobile games and real-world data challenges. Responsibilities include crafting ML models for gameplay features, leveraging real-world data, partnering with product and design teams, optimizing data pipelines, and contributing to ML infrastructure.
Must have:
  • M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or related field
  • 2+ years of experience developing ML systems in production
  • Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn)
  • Experience with applied ML techniques (supervised learning, clustering, deep learning)
  • Strong analytical and problem-solving skills
  • Ability to communicate technical concepts clearly
  • Ability to work in a fast-paced hybrid environment
  • Experience working on cross-functional teams
Good to have:
  • Experience building ML features for mobile games
  • Experience with data processing frameworks (Apache Beam, Apache Spark)
  • Exposure to active learning, recommendation systems, real-time inference
  • Experience with Cloud ML environments (GCP, AWS)
  • Experience with ML development tools (Jupyter Notebooks, MLflow, Kubeflow)
  • Familiarity with geo-contextual modeling
  • Understanding of geospatial data and location-based modeling
Perks:
  • bonus
  • equity
  • benefits

Job Details

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.

If you're passionate about building intelligent features that bridge the digital and physical worlds, and you're ready to push the boundaries of what's possible in real-world location based mobile gaming, we’d love to hear from you!

The total compensation package for this position includes a new hire offer base salary range of $158,200.00 - $185,000.00 + bonus + equity + benefits.

Individual pay within this salary range is determined by work location and additional factors, including assessed job-related skills, experience, and relevant education or training. Your recruiter can answer any questions about new hire total compensation during the hiring process. An overview of benefit offerings for your location can be found on the careers page.

Join the Niantic team!

Niantic's global-scale augmented reality platform and digital map powers spatial computing experiences in the real world. Incubated out of the Maps team at Google, Niantic first created Ingress and then Pokémon GO, a cultural phenomenon and hit game played by tens of millions of people each month. Niantic’s Lightship platform, which powers Pokémon GO, also supports the company's other games including Pikmin Bloom, Peridot and Monster Hunter Now. 

We believe that cultivating a workplace where our people are supported and included is essential to creating great products our community will love. Our mission emphasizes seeking and hiring diverse voices, including those who are traditionally underrepresented in the technology industry, and we consider this to be one of the most important values we hold close.

Niantic is a hybrid first company. We believe that in person interaction and collaboration fosters creativity, a sense of community, and is critical to our future success as a company. Our hybrid work schedules allow for a mix of remote and in-office work.

We're a hard-working, fun, and exciting group who value intellectual curiosity and a passion for problem-solving! We have growing offices located in San Francisco, Sunnyvale, Bellevue, London, Tokyo, and Zürich. #LI-HYBRID

Candidate Privacy Policy

I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic’s Privacy Notice for Job Applicants and Candidates.

If required by law, by submitting my job application I consent to the processing of my information as described in that Notice, including processing information I voluntarily disclose to Niantic, such as health or medical information, race or ethnicity data, and sexual orientation data and, in limited circumstances sharing information with third parties such as references and other third parties that assist in the hiring process.

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About The Company

San Francisco, California, United States (Hybrid)

Sunnyvale, California, United States (Hybrid)

Bellevue, Washington, United States (Hybrid)

Bellevue, Washington, United States (Hybrid)

Tokyo, Japan (On-Site)

Los Angeles, California, United States (Hybrid)

San Francisco, California, United States (Hybrid)

Sunnyvale, California, United States (Hybrid)

Sunnyvale, California, United States (Hybrid)

Bellevue, Washington, United States (Hybrid)

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