Senior Machine Learning Engineer – Search

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DICK'S Sporting Goods

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Retail • Sports • eCommerce

DICK'S Sporting Goods is the largest sporting goods retailer in the United States, offering a wide range of sporting equipment, apparel, and footwear. Committed to enriching communities through sports, DICK'S Sporting Goods also partners with major sports brands like UnderArmour, Patagonia, and Nike to provide high-quality products. The company is dedicated to inclusivity and sustainability, providing resources and support to help athletes and children participate in sports. Headquartered in Pittsburgh, DICK'S is at the forefront of innovative retail and fosters a people-first culture. The company also runs the DICK'S Sporting Goods Foundation, emphasizing the transformative power of sports.

10,000+ employees

Founded 1948

🛒 Retail

⚽ Sports

🛍️ eCommerce

📋 Description

• Architect and implement large-scale search and ranking systems. • Build robust ML pipelines for training, evaluation, and deployment. • Optimize distributed systems for low latency, high throughput, and fault tolerance. • Ensure models are production-ready with monitoring, logging, and automated retraining. • Integrate ML models into search infrastructure (retrieval, ranking, query understanding). • Work with embeddings, transformers, and vector search technologies to improve relevance. • Scale experimentation frameworks to support rapid iteration and safe rollouts. • Design Cloud deployment architecture for deploying ML models as APIs for real-time inference with Caching. • Develop and maintain APIs for machine learning models to facilitate integration with other systems and applications. • Implement observability for search metrics (latency, relevance, clickthrough). • Work closely with the Machine Learning Platform team to develop and maintain the ML platform to meet business and science objectives utilizing cutting edge tools and techniques. • Partner with product managers and data scientists to translate ideas into production systems. • Understand latest research in the field of search and give inputs to enterprise roadmaps to ensure we are on the path to build Best in Class search & relevancy systems.

🎯 Requirements

• Master's Degree or Equivalent Level in quantitative fields like computer science, engineering, physics, mathematics, etc. • 4+ years of experience in software engineering for ML systems (search, recommendation, or large-scale distributed systems). • Experience in API engineering, including designing, developing and maintaining APIs. • Languages & Tools: Python, Java/Scala, C++. • ML Frameworks: TensorFlow, PyTorch. • Data & Infra: Spark, Kafka, Kubernetes, Docker. • Search Systems: Elasticsearch, Solr, or custom retrieval engines. • Solid understanding of distributed systems, APIs, and cloud infrastructure (Azure, AWS, or GCP). • Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.). • Comfortable presenting results to cross functional partners and help them understand technical trade offs. • Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery. • Experience with vector databases and large-scale embedding retrieval. • Familiarity with reinforcement learning for ranking. • Background in eCommerce or consumer-facing search systems. • Strong focus on reliability, scalability, and performance tuning.

🏖️ Benefits

• incentive, equity and benefits • generous suite of benefits