Machine Learning Engineer

The Role:

The Machine Learning team is responsible for designing developing and deploying cutting-edge AI/ML solutions owning the full lifecycle from ideation to production. In this role you will work closely with the ML Platform and Data Science teams to maximize the impact of ML across every area of the business. This is an opportunity to join a growing team and help shape its future direction.

Key Responsibilities:

• Designing & Implementing AI/ML Solutions: Lead the design and implementation of robust scalable and high-performance machine learning applications that power critical user experiences and business operations.

• End-to-End Ownership: Take ownership of the full machine learning lifecycle for various applications working closely with data scientists product managers and backend engineers to define problems develop solutions and measure impact.

• Driving Business Impact: Identify opportunities to apply machine learning to solve complex business challenges directly contributing to key metrics such as user engagement conversion  and overall revenue.

• Leveraging & Contributing to ML Platform: Partner with the Machine Learning Platform team to utilize existing infrastructure and provide critical feedback and requirements to shape the platform's future direction.

• Setting Technical Standards: Champion best practices for MLOps code quality testing and deployment ensuring the reliability and maintainability of our ML application stack.

• Evangelize ML throughout the organization: Communicate results and methodology effectively within the team and to external stakeholders

Key Competencies:

Technical Skills:

• Proven experience in the end-to-end development and deployment of machine learning solutions including successfully transitioning models to production environments.

• Strong programming proficiency particularly in Python and SQL coupled with a solid understanding of software engineering best practices and principles as applied to machine learning system development.

• Experience with cloud platforms such as AWS Azure or GCP and familiarity with MLOps practices.

• Hands-on experience with key machine learning frameworks and libraries (e.g. PyTorch Scikit-Learn XGBoost) and expertise in relevant AI subfields such as Deep Learning Natural Language Processing (NLP) and Computer Vision

• Familiarity with Large Language Models (LLMs) and other advanced AI tools including potential applications of AI agents and a strong interest in staying updated on the latest developments in the field.

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

Minimum Qualifications:

• Experience: 5+ years of industry experience

Preferred Qualifications:

• Education: Bachelors in Computer Science or similar

Performance Metrics:

Direct

Business impact (NARPAU GMV Revenue)

What We can Offer:

• Flexible PTO

• Competitive salary & equity package

• Monthly Gametime credits for any event ($1200/yr)

• Medical dental & vision insurance

• Life insurance and disability benefits

• Diverse Family-forming benefits through Carrot Fertility

• 401k HSA pre-tax savings programs

• Company off-sites and meet-ups

• Wellness programs

• Tenure recognition

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

$195000—$230000 USD