Full-Time

Director – AI/ML Engineer

Updated on 2/3/2025

84.51 Degrees

84.51 Degrees

1,001-5,000 employees

Data analytics for retail and consumer goods

Data & Analytics
Consumer Goods

Compensation Overview

$116k - $266.3kAnnually

+ Variable Compensation

Senior, Expert

Chicago, IL, USA + 1 more

More locations: Cincinnati, OH, USA

Hybrid position requiring in-office attendance on Monday, Tuesday, Wednesday, and Thursday.

Category
Applied Machine Learning
Deep Learning
AI Research
AI & Machine Learning
Required Skills
Kubernetes
Microsoft Azure
Python
Data Science
Tensorflow
Data Structures & Algorithms
Pytorch
Apache Spark
Machine Learning
Docker
Terraform
Databricks

You match the following 84.51 Degrees's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • Bachelor’s degree or higher in Machine Learning, Computer Science, Computer Engineering, Applied Statistics, or related field.
  • 7+ years of experience developing cloud-based software solutions and an understanding of design for scalability, performance, and reliability.
  • 7+ years of experience using advanced algorithms, programming languages, or technologies.
  • 4+ yrs hands-on experience building large-scale ML models, preferably as a data scientist; 2+ years experience in emerging AI preferred.
  • 4+ 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.
Responsibilities
  • Lead and manage a team of 4-5 individuals focusing on AI/ML Engineering, Data Development, and deployment of services into AKS.
  • Foster a collaborative and innovative team environment, encouraging professional growth and development among 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.
  • Provide formal and informal guidance to peer data scientists and engineers within 84.51˚.
  • Apply appropriate documentation, version control, and other internal communication practices across channels.
  • Make time-sensitive decisions and solve urgent problems without escalation.
Desired Qualifications
  • 2+ years experience in emerging AI preferred.
  • 4+ years of experience in tech consulting, retail or related professional services preferred.
  • Knowledge of deep learning methods is highly preferred.

84.51° offers data analytics and marketing services to retailers and consumer goods companies, helping them understand and engage with their customers. By using advanced data science and predictive analytics, the company analyzes consumer data to provide insights into shopping behavior and preferences. Unlike its competitors, 84.51° focuses on a business-to-business model, charging clients for access to its analytics tools and consulting services. The company's goal is to foster a positive workplace culture while enabling clients to make informed marketing decisions.

Company Stage

M&A

Total Funding

$5.5M

Headquarters

Cincinnati, Ohio

Founded

2015

Simplify Jobs

Simplify's Take

What believers are saying

  • Growing demand for omnichannel retail strategies boosts 84.51°'s analytics solutions.
  • Kroger's retail media expansion creates opportunities for 84.51°'s data-driven advertising services.
  • Increased foot traffic in stores allows 84.51° to optimize in-store promotions.

What critics are saying

  • Competition from Albertsons and Walmart may impact 84.51°'s market share.
  • Kroger's in-house advertising platform could create internal competition for 84.51°.
  • Economic uncertainty may reduce demand for premium consumer insights.

What makes 84.51 Degrees unique

  • 84.51° leverages advanced data science to provide deep consumer insights.
  • The company focuses on B2B services, offering analytics to retailers and CPG manufacturers.
  • 84.51° is a wholly owned subsidiary of The Kroger Co., enhancing its retail expertise.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Company Match

401(k) Retirement Plan

Unlimited Paid Time Off

Paid Vacation

Paid Sick Leave

Paid Holidays

Parental Leave

Hybrid Work Options

Mental Health Support