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About This Role
\*\*\* If you have any questions or to connect with a recruiter while your application is being reviewed, please Text DFS3 to 317\-597\-8130 \*\*\*
Equal Opportunity Employer, including disability/vets
Cox Fleet keeps your fleet moving!
Headquartered in Indianapolis, Cox Fleet has grown to become one of the largest fleet maintenance companies in the country.
Cox Fleet is the leading provider of on\-site mobile maintenance and repair services nationwide, offering mobile on\-site fleet service for light medium, and heavy\-duty trucks and trailers. Cox Fleet also services customers utilizing its 50\+ nationwide service centers; each offering accident repair, painting, refurbishment, and heavy mechanical repair. We are supported by a 24/7 in\-house call\-center and provide scheduled maintenance services and unscheduled services to fleets anywhere, anytime.
JOB SUMMARY
Cox Fleet is currently hiring a Shop Trailer Mechanic I. This is a dedicated on\-site shop position and we do not provide emergency side of the road type of repairs. If you are looking for a new place to call home, we would love to talk to you! The Shop Trailer Technician I will be responsible for performing DOT inspections, Preventative Maintenance inspections, light repairs, and other duties as assigned such as trailer brakes, air lines, auxiliary pumps and engines, liftgates, and brake chambers. The Shop Trailer Technician I can perform more advanced repairs under the supervision of a Shop Trailer Technician II or higher. The Shop Trailer Technician I assists Shop Trailer Technician II or higher Technicians with repairs and continues to learn additional advanced mechanical skills and diagnosis. A successful Shop Trailer Technician I complies with all company policies and achieves high level performance metrics.
DUTIES
- Always follows and complies with safe operating practices and procedures.
- Independently determine parts required for each job and interact with the Shop Parts Department to obtain them.
- Maintain a clean and safe work environment. Assist in cleanup at the end of each day for tools, parts, and equipment.
- Applies knowledge that is acquired through formal training or on\-the\-job experience to perform one's job; works with, understands, and evaluates technical information related to the job.
- Work with Service Writer to assess customer needs, providing information or assistance, resolving their problems, or satisfying their expectations.
- Manage concurrent assigned tasks, making effective judgments as to prioritizing work related activities and time allocations.
- Act with integrity, demonstrate honesty and keep commitments. Behave in a consistent manner, keeping sensitive information confidential and adhering to ethical and professional standards.
- Perform scheduled preventative maintenance (“PM”), DOT Inspections and follow up repairs on light, medium and heavy\-duty vehicles in a Shop environment.
- Perform routine maintenance such as changing oil, checking batteries, and lubricating equipment.
- Use hand tools, precision instruments, as well as Trailer tools, welding equipment, lifts and jacks.
- Document according to company standards and upload pictures of work performed, parts used, and all findings observed on Repair Orders (“RO”) using company issued device and/or Karmak application.
- Accurately complete DOT forms and all other forms of documentation in timely fashion.
- Maintain a high level of productivity and be able to work within or close to most Standard Repair Times.
- Communicate with Shop Manager and support team to obtain approvals on repair estimates, retrieve purchase order numbers and/or discuss RO findings notes.
- Perform all work in compliance with organizational safety, health and environmental policies, and federal regulations, to include OSHA, EPA, and DOT.
- Participate and complete all\-in company required safety training.
- Maintain Shop assigned service trucks, conduct safety checks and daily pre/post trip inspections.
- Perform minor adjustment and repairs on various types of trailer equipment and systems including, but not limited to the following: trailer brakes, air lines, auxiliary pumps and engines, liftgates, and brake chambers, Trailer steering systems.
- Adhere to company policies, processes, and procedures.
REQUIREMENTS
- High School Diploma/GED and up to 2 years’ experience in a related field
- Possess and supply a set of hand tools necessary to perform required job duties.
- OEM training and certifications are preferred.
- Participate in and complete all\-in company required training
- This position follows regulations issued by the Department of Transportation’s (DOT) Federal Motor Carrier Safety Administration (FMCSA). Candidate must be able to successfully complete and pass a DOT\-regulated pre\-employment background screening and DOT physical prior to employment.
- A current and valid DOT medical card with more than four (4\) months remaining until its expiration may be submitted in leu of a DOT physical. If the DOT medical card has four (4\) months or less of validity remaining, a DOT physical will be required.
- Safe drivers needed; valid driver’s license required.
REQUIRED CERTIFICATIONS OR OBTAINED WITHIN 18 MONTHS
- ASE T8 (PMI) certification
PREFERRED CERTIFICATIONS
- ASE 608/609 certification\*
SKILLS \& ABILITIES
- Knowledge of trailer parts and systems, including their designs, uses, repair, and maintenance, to make repairs or perform maintenance services.
- Understand the implications of new information for both current and future problem\-solving and decision\-making.
- Ability to lift, bend, climb, stand, and walk for long periods of time; ability to perform moderately heavy laboring work
- Ability to exert oneself physically over long periods of time without tiring, which may include performing repetitive tasks.
- Ability to accurately judge which of several objects is closer or farther away from the observer, or the distance between an object and the observer.
- Ability to communicate information (for example, facts, ideas, or messages) in a succinct and organized manner. Engages in effective two\-way communication with individuals and groups.
- Ability to determine the type of tools and equipment needed.
WHY COX FLEET?
- Weekly pay – get paid every Friday for added convenience and financial flexibility
- Safe driving \& tech efficiency bonuses
- Safety boots \& safety glasses reimbursement
- Extreme weather gear (cold \& hot)
- Uniforms provided with laundry service where available
- Take the service truck home daily (stop paying for gas!)
- Tablet \& company cellphone provided
- Technical training provided to advance your career
- Dedicated career path – Over 50% of our front\-line managers are promoted from within
BENEFITS
- Health, dental, vision insurance starts DAY ONE of employment.
- 401(k) matching starts after 90 days, 100% match up to 6% contribution and an additional 2% discretionary contribution by the company.
- Accrue up to 200 hours (5\-weeks) of Paid Time Off based on your tenure with the company.
- Tuition Assistance/Reimbursement
- Adoption/Surrogacy assistance
- Pet Insurance
- Multiple ERG, diversity groups, and company paid volunteer hours.
- Employee discounts on new vehicle purchases, cellphone plans, ride
*Please note:**This posting is for informational purposes only and does not constitute an official job application.* *To be considered for employment, all candidates must* *submit their application directly through official Cox careers website.* *Applicants who complete Applications that are received through third\-party postings, social media, or other channels will be invited to submit an official Application through the company’s career site.*
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Cox Fleet (Part of Cox Enterprises), this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Cox Fleet (Part of Cox Enterprises) AI Hiring
Cox Fleet (Part of Cox Enterprises) has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Hillsborough, NJ, US, Philadelphia, PA, US.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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