Senior Machine Learning Engineer, Platform

$200,000 - $200,000/Yr

Gametime United - New York, NY

Full-time - Senior

New York, NY

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About the position

The Senior Machine Learning Engineer will be a key member of the Machine Learning Platform team at Gametime, responsible for building and enhancing the core components that support the entire machine learning lifecycle. This role involves close collaboration with ML Engineers and Data Scientists to create powerful, generalized solutions that improve model iteration speed and reliability, ultimately impacting millions of users. As a founding member of the team, the engineer will have the opportunity to shape the future direction of the platform.

Responsibilities

• Collaborate with Machine Learning Engineers and Data Scientists to understand their platform needs and translate them into powerful, generalized solutions.
• Own existing platform systems and develop the next generation of tools such as training, feature, and inference platforms.
• Architect a platform that boosts overall model iteration speed and allows for self-service capabilities for ML Engineers and Data Scientists.
• Improve the reliability of all components of the ML platform that power critical product features.

Requirements

• 5+ years of industry experience in machine learning or related fields.
• Proven track record in designing and implementing mission-critical, high-reliability systems with rapid deployment.
• Outstanding programming proficiency, particularly in Python.
• Strong working knowledge of AWS or equivalent cloud platforms.
• Hands-on experience with industry-standard tools and technologies such as Kafka, Docker, gRPC, DynamoDB, Redis, Temporal, Snowflake, Airflow, and SQL.
• Keen interest in machine learning technologies like PyTorch, Scikit-Learn, XGBoost, and Jupyter.

Nice-to-haves

• Bachelor's degree in Computer Science or a similar field.

Benefits

• Competitive salary range of $200,000 to $230,000 USD based on experience and skills.
• Inclusive work environment that fosters diversity and belonging.