Lead AI/ML Engineer (P2122)

84.51° Overview:

84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

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We are seeking a Lead AI/ML Engineer to join our AI Acceleration team. The AI Acceleration team will enable AI democratization through apps & services and asymmetric growth through embedding generative AI capabilities across our business. The cross-functional talent will help train, optimize, and deploy foundational models and sciences while also engaging with third party vendors to enable speed, scale, and efficiency.  
 

The Lead AI/ML Engineer requires a unique mix of software engineering and machine learning skills necessary to create, deploy and maintain computationally efficient ML implementations, frameworks, tools and end-to-end solutions. This role has a specific focus on emerging artificial intelligence implementation into our tools and platforms. A strong understanding of math, algorithms, ML and data pipelines along with DevOps & MLOps best practices that will scale across many users and/or large, complex, and diverse data sets is critical to success. 
 

Responsibilities: 

• Technical ML Engineer lead on larger projects that can span months 

• Foster a collaborative and innovative team environment, encouraging professional growth and development among junior team members. 

• Leverage known patterns, frameworks, and tools for automating & deploying machine learning solutions 

• Develop new tools, processes and operational capabilities to monitor and analyze model performance and data accuracy where needed 

• Work with researchers to optimize and scale Machine Learning Solutions using best practices in DevOps & MLOps 

• Abstract ML solutions as packages, APIs, or components that could be reused across the business 

• Build, steward, and maintain production-grade solutions (robust, reliable, maintainable, observable, scalable, performant etc.) to manage and serve machine learning models and science solutions 

• Research state of the art artificial intelligence and machine learning algorithms, patterns, processes, and tooling to identify new opportunities for implementation across the enterprise. Serve as early adopter of new machine learning tools, platforms, and processes.  

• Understand business requirements and trade-off scale, risk, and accuracy to maximize value and translate research into consumable products or services  

• Reduce time to delivery, automate ML pipelines, and implement continuous feedback & monitoring practices 

• Responsible for code/science reviews and QA sign off 

• Apply appropriate documentation, version control, and other internal communication practices across channels.   

• Make time-sensitive decisions and solve urgent problems without escalation. 

 
Qualifications, Skills, and Experience: 

• Bachelor’s degree or higher in Machine Learning, Computer Science, Computer Engineering, Applied Statistics, or related field.  

• 4+ years of experience developing cloud-based software solutions and an understanding of design for scalability, performance, and reliability. 

• 4+ years of experience using advanced algorithms, programming languages, or technologies 

• 2+ yrs hands-on experience building large-scale ML models, preferably as a data scientist; 2+ years of experience in emerging AI preferred 

• 2+ years of experience in tech consulting, retail or related professional services preferred 

• Hands-on experience in the full end to end SDLC developing software solutions that scale and leverage CI/CD and MLOps to develop, test, and deploy. 

• Experience building large-scale algorithmic solutions that have been successfully delivered to stakeholders. 

• Excellent communication skills, particularly on technical topics.  

• Strong time and project management skills; the ability to balance multiple, simultaneous work items and prioritize as necessary. 

• Knowledge of deep learning methods is highly preferred. 

• Working experience in one or more ML frameworks such as PyTorch, TensorFlow, MLLib, and MLFlow 

• Knowledge of E2E Machine Learning pipeline and MLOps tools (e.g. Model registry, Experiment tracking, feature store, model monitoring) 

• Hands-on experience with technologies such as Azure, Spark, Nvidia Triton and Databricks 

• Strong skills in Python 

• Kubernetes & Docker experience 

• CI/CD Pipeline experience; Github Actions a plus 

• Terraform experience 

• API development experience a plus 

 

 

IMPORTANT INFO

This is a Hybrid position. Candidates must be able to come into the office on Monday, Tuesday, and Wednesday of each week. We have locations in Cincinnati, OH, Chicago, IL, Deerfield, IL, New York, NY, and Portland, OR. There are no remote options for this position. 

We are NOT working with Staffing Firms, Consulting Companies, or any other 3rd parties on this position. 

Full-time only. No contracts. No C2C. 

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