Remote Staff Machine Learning Infrastructure Engineer

Description:

• StubHub is on a mission to redefine the live event experience globally, catering to both attendees and sellers.
• The company is seeking a Staff Machine Learning Infrastructure Engineer to join the Data Engineering & Analytics team.
• This role focuses on machine learning infrastructure and real-time inference systems.
• The engineer will architect and build foundational ML platforms for recommendation systems, pricing optimization, and personalization.
• As a Staff-level individual contributor, the engineer will set technical direction for ML infrastructure across the organization.
• The position requires balancing long-term technical progress with immediate organizational needs.
• The role is hybrid, requiring 3 days in the office and 2 days remote, based in New York, NY or Los Angeles, CA.
• The engineer will work on modernizing ML infrastructure to support real-time inference, improve feature engineering workflows, and enable faster model deployment.
• Responsibilities include setting technical direction, core ML infrastructure development, technical leadership, and connecting team efforts.

Requirements:

• Candidates must have 8+ years of relevant software or data engineering experience in a fast-paced environment.
• A minimum of 3+ years of experience with machine learning infrastructure, MLOps, or ML platform engineering is required.
• Proven track record of setting technical direction and leading complex, multi-team initiatives is essential.
• Strong programming and analytical skills with expertise in Python, Scala, or Java, and infrastructure-as-code are necessary.
• Experience with feature store services and their interoperability between batch and live inference systems is required.
• Candidates should have experience with live inference services, including caching, SLAs, and performance optimization for production ML workloads.
• Experience with model lifecycle management, including versioning, A/B testing, and rollback capabilities is needed.
• Familiarity with streaming systems (Spark, Kafka) and cloud-based ML platforms (AWS SageMaker, Google Vertex AI, or Azure ML) is required.
• Experience mentoring engineers and establishing technical best practices across teams is essential.
• Candidates should possess strong technical leadership, strategic thinking, cross-functional collaboration, and communication skills.

Benefits:

• The position offers an accelerated growth environment designed for swift skill and knowledge enhancement.
• A top-tier compensation package is provided, including enticing stock incentives.
• Employees enjoy unlimited Flex Time Off, promoting a healthy work-life balance.
• A comprehensive benefits package is available, featuring 401k, and premium Health, Vision, and Dental Insurance options.
• The anticipated gross base pay range for this role is $300,000 - $350,000 USD, with actual compensation varying based on qualifications and experience.