Lead Machine Learning Engineer (REMOTE)
Remote - US, United States
DICK'S Sporting Goods
At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve.
If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today!
OVERVIEW:
Founded in 1948, DICK’S Sporting Goods first started as a bait-and-tackle shop in Binghamton, NY and has since rapidly expanded into a leading omnichannel retailer with more than 850 locations representing our multiple brands: DICK’S, House of Sport, Golf Galaxy, Public Lands, Going Going Gone, and more. Over the years, it’s been our relentless focus on inspiring, supporting and equipping athletes and outdoor enthusiasts to achieve their dreams that has allowed us to become the $13B company we are today.
Our company is looking to invest in our future as we embark on a journey from being the best sports retailer in the world to becoming the best sports company in the world. We aim to build the ultimate athlete data set that will power our tools and platforms for the most personalized athlete experiences. Join us as we transform our technology, data and analytics to build next-gen tools and platforms for our athletes and teammates.
About the Position:
Are you a passionate technologist with experience in AI, Machine Learning, Data Science and Analysis? Are you looking for an opportunity to drive enterprise impact and shape the future of a leading sports retailer with $12B+ in revenue and 800+ physical stores? Do you enjoy working with a highly skilled team of Machine Learning engineers & Scientists, co-creating enterprise grade AI capabilities?
As the Lead Machine Learning Engineer (Decision Engine/Performance Platform), you will be a key technical leader in our athlete and teammate transformation that aims to deliver a best in class customer experience through highly skilled teammates by providing them advanced intelligent decisioning tools using AI/GenAI and Machine Learning at its core. This is an exceptional opportunity to transform the way we make omnichannel enterprise decisions through building foundational AI/GenAI capabilities and do career defining work in the space.
There are two specific openings, one in the area of Decision Engine and the other in Performance Platform.
In Decision Engine, the emphasis is more on experience building enterprise decisioning systems using AI and integrating across multiple enterprise systems for decision delivery.
While in Performance Platform, the focus is more on building sports mechanics and performance related experiences using AI.
Job Purpose:
This role will require an emerging technical leader & SME with strong experience in traditional Machine Learning algorithms along with deep understanding of the cutting edge SOTA AI/GenAI methods used in recommender systems, enterprise decisioning tools and/or computer vision/ sports mechanics. As a technical leader, you will be influencing critical enterprise technical strategies both in the Machine Learning/AI space and neighboring integration spaces like frontend, DSP, backend data systems etc. You will partner with product, business, and engineering leads to design systems for future growth and scale and help them understand the art of the possible with AI technology through deep technical design.
Responsibilities:
Design and lead ML architecture and model deployment strategies for both batch and streaming use cases
Ensure the scalability, reliability, and efficiency of machine learning solutions.
Optimize and improve the performance of existing machine learning models and systems.
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.
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
Conduct research and stay up-to-date with the latest advancements in machine learning and artificial intelligence, specifically in the areas of recommender systems and/or computer vision
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Decision Engine – Understand other recommender/search systems within the enterprise including but not limited to internal systems and external systems like Adobe, Elastic etc and how they will interact with the enterprise decision engine
Performance Platform – Understand the market offerings in performance science & develop a perspective on Dick’s unique technical positioning of the performance platform using computer vision, performance mechanics and AI.
Job Requirements:
6+ years of experience in the field with at least 2-3 years of being the main technical lead in related projects (strongly preferred)
Experience being the technical lead of multiple projects at the same time, responsible for delivery and business metrics
Experience in API engineering, including designing, developing and maintaining APIs
Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain
Expert understanding of Python and other common languages.
Expert level experience in big data technologies including but not limited to Spark, Kafka, distributed systems computing etc.
Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.)
Previous experience mentoring, training, and developing junior members of the team through technical influence.
Experience with software engineering principles as it relates to Machine Learning systems.
Comfortable presenting results to and influencing senior and executive leadership on strategic technical decisions, from the lens of science.
Deep understanding of SOTA machine learning models in the overall retail space and performance space. Bonus if specific experience in cutting edge recommender systems, computer vision and sports science.
Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.
QUALIFICATIONS:
Education: Master's Degree or equivalent level preferred in quantitative fields like Computer Science, Engineering, Physics, Mathematics, etc.
General Experience: Wide and deep experience providing expert competence (Over 10 years to 15 years)
#LI-FD1
Targeted Pay Range: $95,200.00 - $158,800.00. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay.DICK'S Sporting Goods complies with all state paid leave requirements. We also offer a generous suite of benefits. To learn more, visit www.benefityourliferesources.com.Tags: Agile APIs Architecture Azure Big Data Computer Science Computer Vision CX Deep Learning DevOps Distributed Systems Engineering Generative AI Jira Kafka LangChain Machine Learning Mathematics ML models Model deployment OpenAI Physics Python PyTorch Recommender systems Research Spark Streaming TensorFlow
Perks/benefits: Career development Competitive pay Equity / stock options Salary bonus
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