Lead AI​/ML Engineer; P4645

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.

84.51° follows a 5‑day in‑office work schedule to support collaboration, alignment, and team connection.

As a Lead AI/ML Engineer (G3) on the Labs team, you will serve as a hands‑on technical lead at the intersection of classical optimization science and modern AI/ML. Our Labs team has a strategic focus on building AI‑enhanced optimization systems, designing AI layers that augment, accelerate, and extend classical optimization engines to unlock solutions that neither approach achieves alone. This is not a generalist ML role: you will bring deep optimization foundations and use them as the platform on which the next generation of intelligent, adaptive systems are built.

You will contribute code daily, serve as one of the team's primary subject‑matter experts on optimization formulations, solver selection, and hybrid architecture design, mentor engineers and researchers, and partner with cross‑functional stakeholders to define, deliver, and scale production systems across Kroger.

• Serve as a hands‑on developer responsible for building and maintaining end‑to‑end ML, AI, and optimization‑based solutions
• Design and build hybrid AI/optimization systems including ML‑guided search, learned warm starts, neural network surrogate models, and AI‑augmented constraint formulations that improve the performance, scalability, interpretability and adaptability of classical optimization solvers
• Lead technical design, implementation, and review processes for POCs and production‑ready systems
• Lead end‑to‑end solution lifecycle—from rapid prototyping through to scaling and hand‑off to production teams in partnership with other data scientists and engineers within Labs and across the business
• Serve as one of the team's primary technical resources on optimization problem formulations, solver selection, and performance benchmarking across constraint types and problem scales
• Partner with researchers and data scientists to co‑develop, scale, and operationalize new algorithms
• Architect and implement robust ML(AI)
  Ops pipelines that support experimentation, deployment, and monitoring
• Build reusable ML components and APIs that enable modularity and scalability across business areas
• Evaluate and adopt emerging technologies and tooling that can enhance experimentation and delivery speed
• Drive technical best practices in code quality, documentation, observability, and team knowledge sharing
• Drive experimentation and benchmarking to select performant solutions that balance complexity and business value
• Contribute to Labs’ collaborative, research‑forward culture by learning, sharing, and mentoring both junior and senior engineers and researchers on industry‑leading and cutting‑edge technologies
• Lead and participate in code reviews and technical architecture planning to ensure adherence to preferred patterns and standards
• Represent Labs in technical forums; proactively mentor junior and peer engineers
• Collaborate with product and business stakeholders to align technical execution with innovation goals

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Applied Mathematics, or a related field
• 4+ years experience developing ML, AI, or optimization systems, including production deployment and scaling
• Strong software engineering fundamentals and daily coding experience in Python
• Deep proficiency in Python and fluency in Num Py, pandas, PySpark and at least 3 of the following ML and Optimization libraries - PyTorch, Tensor Flow, scikit‑learn, and Pyomo (Pyomo proficiency is specifically required).
• Hands‑on experience architecting and product ionizing at least one type of optimization problem (e.g., network optimization, vehicle routing, scheduling, facility location, or resource allocation)
• Practical experience with at least two industry‑standard optimization solvers such as Gurobi, CPLEX, OR‑Tools, Pyomo, PuLP, CBC, or…