AI Transformation Engineer (Mon-Fri 8:00am-4:30pm) at RK Logistics Group, Inc

Chandler, Arizona, United States -

Full Time

Start Date

Immediate

Expiry Date

24 Jun, 26

Salary

110000.0

Posted On

26 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Pandas, NumPy, PyTorch, TensorFlow, Scikit-learn, Software Engineering, Machine Learning Deployment, Rapid Prototyping, Data Manipulation, Intelligent Routing, Predictive Intelligence, Simulation, Code Scalability

Industry

Logistics;Transportation;Supply Chain and Storage

Description

Description About RK Logistics Group & Project Catalyst RK Logistics Group is a leading Silicon Valley-based supply chain solutions provider. We are embarking on a massive, industry-defining initiative: Project Catalyst. Inspired by the most aggressive tech-driven acquisition models, we are building a dedicated "RK AI Lab" to acquire traditional, legacy logistics companies and fundamentally transform them using artificial intelligence. We are looking for brilliant, ambitious recent college graduates to join the RK AI Lab. You won't just be maintaining legacy code; you will be part of an elite "integration team" deploying our proprietary AI Transformation Stack to newly acquired companies, driving massive operational overhauls in 90-120 day sprints. If you want to see your code directly impact the physical world—optimizing routes, powering digital twins, and deploying autonomous robotics—this is the place for you. Role Summary As an AI Transformation Engineer on Project Catalyst, you will bridge the gap between cutting-edge machine learning models and real-world physical operations. You will work alongside senior data scientists and logistics experts to build and deploy intelligent systems across our growing portfolio of acquired companies. This role is highly dynamic, blending software engineering, machine learning deployment, and hands-on operational problem solving. Requirements Key Responsibilities Deploy the AI Stack: Assist the integration team in deploying our AI Transformation Stack (intelligent routing, automated dispatch, and predictive intelligence) to newly acquired logistics companies. Model Training & Fine-Tuning: Help train and refine proprietary machine learning models using vast amounts of real-world supply chain data, creating compounding network effects across our portfolio. Collaborate on Digital Twins: Work closely with senior engineers to develop Supply Chain Digital Twins, running simulations to stress-test warehouse layouts and fleet operations before physical execution. Automate Legacy Processes: Write clean, scalable code to replace manual, paper based workflows with automated, AI-driven solutions (e.g., digital proof of delivery, automated billing). Rapid Prototyping: Work in 90-120 day transformation sprints, rapidly prototyping and iterating on AI tools that deliver immediate, measurable ROI. Qualifications & Skills Education: Recent graduate (Class of 2025 or 2026) with a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Operations Research, or a related highly quantitative field. Programming: Strong proficiency in Python. Familiarity with SQL and data manipulation libraries (Pandas, NumPy). AI/ML Knowledge: Academic, project, or internship experience with machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Problem Solving: A builder’s mindset. You enjoy tackling complex, messy real-world problems and turning them into elegant, automated solutions. Communication & Travel: Ability to communicate technical concepts to non-technical operational staff at newly acquired companies. Willingness to travel up to 25% to regional facilities to oversee technology deployment. Agility: Ability to thrive in a fast-paced, startup-like environment within a larger established company. You are excited by the prospect of transforming traditional industries. Benefits & Perks Competitive entry-level base salary with performance-based bonuses tied to successful acquisition transformations. Comprehensive Health, Dental, and Vision Insurance. 401(k) Plan with Company Match. Modern, collaborative office environment in Phoenix, AZ. Accelerated Career Growth: Get in on the ground floor of the RK AI Lab. As the portfolio grows, your leadership opportunities will scale rapidly. Direct mentorship from senior AI leaders and logistics industry veterans. RK Qualities & Commitment to Diversity Adherence to all RK Safety, Quality, ISO, and HR policies and standards. RK Logistics Group is an equal opportunity employer committed to fostering an inclusive, innovative environment. We encourage candidates from all backgrounds to apply. RK Logistics Group will consider qualified applicants with a criminal history pursuant to the California Fair Chance Act and applicable local regulations. You do not need to disclose your criminal history or participate in a background check until a conditional job offer is made to you. After making a conditional offer and running a background check, if RK Logistics Group is concerned about a conviction that is directly related to the job, you will be given the chance to explain the circumstances surrounding the conviction, provide mitigating evidence, or challenge the accuracy of the background report. Find out more about the Fair Chance Act by visiting calcivilrights.ca.gov/fair-chance-act. RK Logistics Group is an Equal Opportunity Employer committed to fostering a diverse, inclusive, and respectful workplace. We do not discriminate in employment decisions or practices based on race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, age (40 or older), disability, genetic information, veteran status, or any other legally protected status under applicable federal, state, or local laws.

Responsibilities

The engineer will deploy the proprietary AI Transformation Stack, including intelligent routing and predictive intelligence, to newly acquired logistics companies. They will also assist in training proprietary machine learning models using supply chain data and developing Supply Chain Digital Twins.