Senior Machine Learning Engineer, Platform in New York

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Job DescriptionJob DescriptionAbout Us:Live experiences help people cross today's digital divide and focus on what truly connects us – the here, the now, this once-in-a-lifetime moment that's bringing us together. To fulfill Gametime's mission of uniting the world through shared experiences, we make it easy for people to discover and access the live experiences that matter most.With platforms on iOS, Android, mobile web and desktop supporting more than 60,000 events across the US and Canada, we are reimagining the event ticket industry in order to move at the speed of life.The Role:

The Machine Learning Platform team is responsible for building the core components necessary to support and accelerate the full machine learning lifecycle. In this role, you will work closely with ML Engineers and Data Scientists as well as the Data Platform and Backend Engineering teams to maximize the impact of ML. At Gametime, the modeling teams are expected to work full-stack and end-to-end. This requires reliable, powerful infrastructure and abstractions provided by the Machine Learning Platform team. This is an opportunity to join as a founding member of the team and help shape its future direction.

Above & Beyond: The Impact You'll Make:

• 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 of tools (e.g. training platform, feature platform, inference platform)
• Architect a platform that boosts overall model iteration speed and allows Machine Learning Engineers and Data Scientists to work in a self-serve manner
• Improve the reliability around all components of an ML platform capable of powering critical product features used by millions of users

Always Be Curious: Skills You've Learned Along The Way:Technical Skills:

• Proven track record in designing and implementing mission-critical, high-reliability systems with rapid deployment
• Outstanding programming proficiency, with particular expertise in Python
• Strong working knowledge of AWS or equivalent cloud platforms
• Hands-on experience with industry-standard tools and technologies (e.g., Kafka, Docker, gRPC, DynamoDB, Redis, Temporal, Snowflake, Airflow, SQL)
• Keen interest in machine learning and its associated technologies (such as PyTorch, Scikit-Learn, XGBoost, Jupyter), preferably with some practical experience

Interpersonal Skills:

• Ability to collaborate effectively across teams and communicate with key stakeholders

Problem-Solving and Decision-Making:

• A proactive self-starter with a strong ability to learn quickly and work independently, demonstrating the desire and readiness to manage an increasing level of responsibility

One Team, One Dream: What We Need To Work Together:

• Experience: 5+ years of industry experience

Qualifications:

• Education: Bachelors in Computer Science or similar

At Gametime pay ranges are subject to change and assigned to a job based on specific market median of similar jobs according to 3rd party salary benchmark surveys. Individual pay within that range can vary for several reasons including skills/capabilities, experience, and available budget.

United States - Pay Range$195,000—$230,000 USD

Gametime is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone can thrive, feel a sense of belonging, and do great work together. As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their , , , veteran status, , parental status, or expression, transgender status, , , , or genetic information. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering across our company.

If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.