84.51˚
Overview
Lead AI/ML/Optimization Engineer (G3) – Labs Innovation Focus. As a Senior AI/ML Engineer on the Labs team, you will serve as a hands-on technical lead responsible for both implementing robust code and guiding the architectural direction of ML/AI/optimization-based systems. This role blends deep engineering expertise, applied ML and optimization research, and system design to accelerate the transition from proof-of-concept to scalable business solution. You will contribute code daily, mentor junior engineers, and collaborate with cross-functional partners to define, deliver, and scale the next generation of AI/ML/optimization capabilities across Kroger.
Company: 84.51° – a retail data science, insights and media company powering Kroger Precision Marketing and related solutions.
Responsibilities
Serve as a hands-on developer responsible for building and maintaining end-to-end ML, AI, and optimization-based solutions
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
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
Lead and participate in code reviews and technical architecture planning to ensure adherence to preferred patterns and standards
Represent Labs in technical forums; mentor junior and peer engineers
Collaborate with product and business stakeholders to align technical execution with innovation goals
Required Qualifications
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 NumPy, pandas, PySpark and at least 3 of the following ML/ML and optimization libraries: PyTorch, TensorFlow, scikit-learn, Pyomo
Hands-on experience architecting and productionizing at least one type of optimization problem (e.g., network optimization, vehicle routing, scheduling, facility location, or resource allocation)
Practical experience with at least one industry-standard optimization solver such as Gurobi, CPLEX, OR-Tools, Pyomo, PuLP, CBC, or SCIP
Hands-on experience designing CI/CD and MLOps workflows using tools such as MLflow, Azure ML, or Databricks
Familiarity with cloud platforms (Azure preferred), containerization (Docker), and orchestration (Kubernetes)
Experience with modern software development practices including testing, logging, observability, and version control
Ability to lead projects through ambiguity and collaborate in highly cross-functional teams
Preferred Experience
Strong track record of partnering with researchers to translate early-stage ML ideas into deployable systems
Experience prototyping and scaling AI solutions in applied environments
Experience designing experiment platforms or reusable ML/optimization infrastructure
Demonstrated leadership in evaluating trade-offs between performance, complexity, and maintainability
Familiarity with real-time or batch data processing systems
Leadership in navigating trade-offs between performance, complexity, and long-term maintainability
Pay Transparency And Benefits
The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.
Benefits include Health (medical, dental, vision) with in-network and out-of-network options; 401(k) with Roth option and matching; Health Savings Account with matching contribution; AD&D and supplemental insurance options.
Hybrid work environment; paid time off with 5 weeks of vacation, wellness days, floating holidays, company-paid holidays, and paid leave for maternity, paternity, and family care.
Pay Range $121,000—$201,250 USD
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Business Consulting and Services
Referrals increase your chances of interviewing at 84.51˚ by 2x
Cincinnati, OH
#J-18808-Ljbffr
Lead AI/ML/Optimization Engineer (G3) – Labs Innovation Focus. As a Senior AI/ML Engineer on the Labs team, you will serve as a hands-on technical lead responsible for both implementing robust code and guiding the architectural direction of ML/AI/optimization-based systems. This role blends deep engineering expertise, applied ML and optimization research, and system design to accelerate the transition from proof-of-concept to scalable business solution. You will contribute code daily, mentor junior engineers, and collaborate with cross-functional partners to define, deliver, and scale the next generation of AI/ML/optimization capabilities across Kroger.
Company: 84.51° – a retail data science, insights and media company powering Kroger Precision Marketing and related solutions.
Responsibilities
Serve as a hands-on developer responsible for building and maintaining end-to-end ML, AI, and optimization-based solutions
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
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
Lead and participate in code reviews and technical architecture planning to ensure adherence to preferred patterns and standards
Represent Labs in technical forums; mentor junior and peer engineers
Collaborate with product and business stakeholders to align technical execution with innovation goals
Required Qualifications
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 NumPy, pandas, PySpark and at least 3 of the following ML/ML and optimization libraries: PyTorch, TensorFlow, scikit-learn, Pyomo
Hands-on experience architecting and productionizing at least one type of optimization problem (e.g., network optimization, vehicle routing, scheduling, facility location, or resource allocation)
Practical experience with at least one industry-standard optimization solver such as Gurobi, CPLEX, OR-Tools, Pyomo, PuLP, CBC, or SCIP
Hands-on experience designing CI/CD and MLOps workflows using tools such as MLflow, Azure ML, or Databricks
Familiarity with cloud platforms (Azure preferred), containerization (Docker), and orchestration (Kubernetes)
Experience with modern software development practices including testing, logging, observability, and version control
Ability to lead projects through ambiguity and collaborate in highly cross-functional teams
Preferred Experience
Strong track record of partnering with researchers to translate early-stage ML ideas into deployable systems
Experience prototyping and scaling AI solutions in applied environments
Experience designing experiment platforms or reusable ML/optimization infrastructure
Demonstrated leadership in evaluating trade-offs between performance, complexity, and maintainability
Familiarity with real-time or batch data processing systems
Leadership in navigating trade-offs between performance, complexity, and long-term maintainability
Pay Transparency And Benefits
The stated salary range represents the entire span applicable across all geographic markets from lowest to highest. Actual salary offers will be determined by multiple factors including but not limited to geographic location, relevant experience, knowledge, skills, other job-related qualifications, and alignment with market data and cost of labor. In addition to salary, this position is also eligible for variable compensation.
Benefits include Health (medical, dental, vision) with in-network and out-of-network options; 401(k) with Roth option and matching; Health Savings Account with matching contribution; AD&D and supplemental insurance options.
Hybrid work environment; paid time off with 5 weeks of vacation, wellness days, floating holidays, company-paid holidays, and paid leave for maternity, paternity, and family care.
Pay Range $121,000—$201,250 USD
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Business Consulting and Services
Referrals increase your chances of interviewing at 84.51˚ by 2x
Cincinnati, OH
#J-18808-Ljbffr