Staff Software Engineer - Ai/ml Platform

Responsibilities

• Architect, design, and implement a scalable AI/ML platform that seamlessly integrates with existing CI/CD pipelines and data platforms, ensuring optimal performance and reliability
• Lead the development of E2E machine learning pipelines for both structured data and Large Language Models (LLMs), tailored for internal platform use cases
• Conceptualize, Design and implement innovative LLM applications to enhance developer productivity, system efficiency, cost-effectiveness across the platform ecosystem.
• Develop, identify and maintain low-code automated tools and frameworks for end-to-end machine learning processes, including model training, model testing, model registration, model deployment, model monitoring, experiment tracking etc.
• Optimise core data pipelines to handle high-volume, high-velocity data flows for training and deploying ML models keeping compliance checks etc.
• Develop comprehensive, high-quality documentation, including detailed technical architecture/design documents, developer-friendly guides, and clear operational procedures to ensure knowledge transfer and system maintainability
• Collaborate closely with data scientists, software engineers, and cross-functional teams to ensure operational excellence and architectural alignment across the organisation
• Lead code reviews, promote best coding practices, mentor junior team members and ensure high code quality standards across the team
• Stay abreast of the latest advancements in AI/ML technologies and MLOps practices, and drive innovation within the organisation

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 7+ years of total industry experience with at least 3+ years in AI/ML operations and/or platform development
• Proficiency in at least one programming language such as Java/Python/GoLang/Scala etc. and familiarity with ML libraries like TensorFlow, PyTorch, or Scikit-learn etc.
• Hands-on experience with infrastructure as code, i.e., Terraform stack.
• Advanced knowledge of AWS cloud services, including but not limited to: Sagemaker, Lambda, S3, Glue, Redshift, EC2, IAM etc.
• Experience in working on at least 1 production level end-to-end AI/ML powered use case
• Familiarity with large language models (LLMs) and generative AI, including experience with AWS Bedrock, Google Vertex or similar platforms
• Familiarity with Kubernetes for container orchestration and Airflow DAGs for workflow orchestration
• Huge plus - relevant certification(s) such as AWS Machine Learning Specialty, or Google Cloud Professional Machine Learning Engineer etc.
• Excellent problem-solving and analytical skills
• Strong communication and collaboration abilities

Fanatics Commerce has a broad range of online, sports venue, and vertical apparel partnerships worldwide, including comprehensive partnerships with leading leagues, teams, colleges, and sports organizations across the world—including the NFL, NBA, MLB, NHL, MLS, Formula 1, and Australian Football League (AFL); the Dallas Cowboys, Golden State Warriors, Paris Saint-Germain, Manchester United, Chelsea FC, and Tokyo Giants; the University of Notre Dame, University of Alabama, and University of Texas; the International Olympic Committee (IOC), England Rugby, and the Union of European Football Associations (UEFA).