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Fleet Optimization Engineer Jobs (NOW HIRING)

Kodiak Gas Services, Inc.

Support fleet optimization initiatives through performance analysis, reliability improvements ... Professional Engineer (PE) license preferred but not required.**Work Experience*** 7-12 years of ...

KLA-Belgium

Fleet Engineer

Phoenix, AZ · On-site

$23.75 - $32/hr

The successful fleet engineer will be responsible for measuring fleet performance, discovering opportunities for optimal availability and throughput, capturing and documenting insights and analysis.

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How much do fleet optimization engineer jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for fleet optimization engineer in the United States is $59.65, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $73.56 per hour, depending on experience, location, and employer.

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Infographic showing various Fleet Optimization Engineer job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $124,067 per year, or $59.6 per hour.

AI Scientist - Transportation & Logistics

San Francisco, CA • Hybrid

Avathon
11 - 50 employees
Learn more about Avathonexternal

Full-time

Posted 20 days ago

Key responsibilities

  • Design and implement advanced AI/ML models for fleet optimization, vehicle routing, scheduling, and demand forecasting.

  • Build solutions for maritime logistics, container repositioning, and multimodal transportation routing, incorporating real-world constraints.

  • Collaborate with engineering teams to deploy AI models into production, ensuring robustness, explainability, and monitoring.

Job description

Who We Are & Why Join Us

Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries -- energy, mining, manufacturing, aerospace, defense, and logistics -- accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale.

Cutting-Edge AI Innovation -- Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment -- Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact -- Work on AI-driven projects that drive real change across industries and improve lives.

Learn more at: avathon.com

 
About the Role

About Avathon

We're hiring a AI Scientist (Transportation & Logistics) at Avathon — where AI meets the real world.
This is a high-impact role at the intersection of operations research, reinforcement learning, and large-scale data systems, focused on building intelligent solutions that transform transportation and logistics networks.

We are looking for an experienced AI Scientist to lead the design and deployment of advanced optimization and machine learning systems across complex transportation ecosystems. You will work on real-world challenges such as routing, scheduling, network optimization, demand forecasting, and asset utilization across multimodal logistics environments including FCL, LCL, FTL, LTL, intermodal, and maritime transportation.

This role offers the opportunity to drive innovation in vessel scheduling, container repositioning, fleet optimization, and dynamic routing, while collaborating closely with engineering, product, and operations teams to bring scalable AI solutions into production.

Key Responsibilities 

AI/ML Model Development 

  • Design and implement advanced models for: 
  • Fleet optimization and capacity planning 
  • Vehicle routing and scheduling (VRP, TSP variants) 
  • Demand forecasting and optimization 
  • Apply reinforcement learning, optimization algorithms, and hybrid ML + OR approaches 

Transportation Domain Solutions 

Build solutions for: 

  • Maritime logistics (vessel scheduling, port operations) 
  • Container repositioning and imbalance optimization 
  • Truckload (FTL), less-than-truckload (LTL), and intermodal routing 
  • Incorporate real-world constraints (time windows, capacity, regulations, SLAs) 

AI Engineering & Deployment 

  • Productionize models using scalable architectures (cloud-native, APIs) 
  • Collaborate with engineering teams to deploy AI solutions into production 
  • Ensure robustness, explainability, and monitoring of models 

Data & Feature Engineering 

Work with large-scale datasets: 

  • Shipment data, GPS/telematics, weather, port congestion, tariffs 
  • Build feature pipelines and data validation frameworks 

Leadership & Strategy 

  • Lead AI initiatives and mentor junior scientists 
  • Translate business problems into AI solutions 
  • Partner with product, operations, and stakeholders to define roadmaps 

Required Qualifications 

  • PhD in Computer Science, Operations Research, Applied Math, or related quantitative field 
  • 6+ years of experience in AI/ML or optimization, or Supply Chain planning systems

Strong expertise in: 

  • Python (NumPy, Pandas, PyTorch/TensorFlow) 
  • Optimization tools (Gurobi, CPLEX, OR-Tools) 
  • Deep knowledge of: 
  • Routing algorithms (VRP, shortest path, heuristics/metaheuristics) 
  • Time-series forecasting and probabilistic modeling 
  • Experience deploying models in production environments 

Preferred Qualifications 

  • Experience in transportation, logistics, or supply chain domain 
  • Familiarity with Maritime shipping or fleet scheduling 
  • Container logistics and repositioning problems 

Experience with: 

  • Reinforcement learning for dynamic decision-making 
  • Digital twins and simulation systems 
  • Knowledge of cloud platforms (GCP, AWS, Azure) 
  • Experience with streaming data (Kafka, Spark) 

Key Skills 

  • Optimization + Machine Learning hybrid modeling 
  • Strong problem-solving and mathematical modeling skills 
  • Ability to handle ambiguous, real-world constraints 
  • Communication skills to explain complex models to business stakeholders 

Publications / Patents: 

  • Strong plus if you have published in AI/ML/OR conferences (NeurIPS, ICML, INFORMS, etc.) 

Interview Process

As part of the interview process, you will be asked to complete a technical assessment. Expect atleast two-three rounds of Technical interviewing rounds and one onsite round.  

Contract and temporary roles are not eligible for the above benefits.

Location: This role is not remote. Candidates must be based in Bengaluru and are expected to report to our Pleasanton office 5 days a week.

Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.

Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.