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About This Role
At Manheim (a Cox Automotive company), we strive to make sure every customer is completely satisfied when they do business with us. On the off chance we fall short, we do our best to make things right, pronto. That's where you come in!
We're looking for an Auto Claims Specialist I to learn the ropes of resolving customer complaints and ensuring we don't make the same mistake again. Do you have the skills we're looking for? Keep reading for more details!
Benefits:
- We all have lives and responsibilities outside of work. We have an exceptional work/life balance at Cox, with flexible time\-off policies.
- We show our appreciation for our talent with a competitive salary package and top\-notch bonus \& incentive plans.
- How does a great healthcare benefits package from day one sound? Multiple options are available for individuals and families. One employee\-only plan could be FREE, if you participate in our health screening program.
- 10 days of free child or senior care through your complimentary Care.com membership.
- Generous 401(k) retirement plans with up to 6% company match.
- Employee discounts on hundreds of items, from cars to computers to continuing education.
- Looking to grow your family? You'll have access to our inclusive parental leave policies, plus comprehensive fertility coverage and adoption assistance.
- Want to volunteer in your community? We encourage that and even offer paid hours for you to do so.
- We all love our pets\-whether they walk, crawl, fly, swim or slither\-and we're happy to supply insurance for them as well.
At Cox, we believe in being transparent \-
What You'll Do:
From your very first day on the job, you'll receive guidance and coaching so you can learn the ropes. You'll work with everyone from buyers to sellers to dealers in coordinating and validating customer returns and claims. With Guidance, responsibilities include:
- Reviews customer claims to verify that they meet Manheim's National Arbitration policies and any account\-specific guidelines.
- Investigates basic, less complex cases (e.g., late title claims, basic condition report claims, vehicle availability, post\-sale inspection fails, mechanical/structural/undisclosed vehicle damage, etc.) or those requiring more prescriptive decision\-making.
- Interfaces with all departments involved in the complaint (i.e., reconditioning, front office, dealer services, vehicle entry, etc.), including during the fact finding and investigative phases.
- Uses appropriate resources to investigate and facilitate relevant inspection, documentation, and communication to ensure appropriate actions are completed to move cases forward or to resolution.
- Uses appropriate levels/limits of financial approval authority to resolve cases.
- Evaluate claims by obtaining, comparing, evaluating, and validating various forms of information.
- Prepares and facilitates communication for resolution via telephone, email, and in\-person discussion.
- Mediates disputes and negotiates repair and/or pricing of disputed vehicles to arrive at a mutually acceptable solution and to keep vehicles sold.
- Monitors and maintains accurate files for each arbitration case, verifying the accuracy of all required documentation, including invoices and settlement agreements.
- Engages with supervisor/manager to determine if escalation is required.
- Performs other duties as assigned.
Who You Are:
You've got a knack for negotiation. You're ethical, dependable, and trustworthy. You're eager to learn. You also have the following qualifications:
Minimum:
- High School Diploma/GED
- Generally, less than 2 years of experience.
- Accuracy and attention to detail.
- Organizational and time management skills.
- The ability to adapt in a fluid and changing environment.
Preferred:
- 1\+ years of automotive or body shop experience.
- Claims adjuster experience.
Cox is a great place to be, wouldn't you agree? Apply today!
USD 19\.90 \- 29\.81 per hour
Compensation:
Hourly pay rate is in the range of $19\.90 \- $29\.81/hour. The hourly base rate may vary within the anticipated range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include commission (annual, monthly, etc.) and/or an incentive program.
Benefits:
Employees are eligible to receive a minimum of sixteen hours of paid time off every month and seven paid holidays throughout the calendar year. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship.
Salary Context
This $39K-$60K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $100K across 15465 roles with salary data).
View full AI/ML Engineer salary data →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 Automotive, 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. This role's midpoint ($49K) sits 70% below the category median. Disclosed range: $39K to $60K.
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 Automotive AI Hiring
Cox Automotive has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Riverside, CA, US, New Castle, DE, US, Matteson, IL, US. Compensation range: $60K - $100K.
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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