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About This Role
Job Description
AI Development Engineer
Requisition ID: 4181
Job Location: TEMPE \- Arizona \- United States
Category for Job Posting: Engineering and Technical
Job Type for Job Posting: Full Time
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About Us
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Innovation. Sustainability. Productivity. This is how we are Breaking New Ground in our mission to sustainably advance the noble work of farmers and builders everywhere. With a growing global population and increased demands on resources, our products are instrumental to feeding and sheltering the world.
From developing products that run on alternative power to productivity\-enhancing precision tech, we are delivering solutions that benefit people – and they are possible thanks to people like you. If the opportunity to build your skills as part of a collaborative, global team excites you, you’re in the right place.
Grow a Career. Build a Future!
Be part of this company at the forefront of agriculture and construction, that passionately innovates to drive customer efficiency and success. And we know innovation can’t happen without collaboration. So, everything we do at CNH Industrial is about reaching new heights as one team, always delivering for the good of our customers. \#LI\-DNI
Key Responsibilities
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Duties : The AI Development Engineer at CNH Industrial America LLC in Tempe, AZ will assist in developing innovative new products to solve problems using AI techniques, such as Machine Learning and Deep Learning to drive AI advancements in new product development and provide continual refinement of existing products. Generating software systems derived from various Machine Learning (ML) techniques to drive innovation. Generating software systems derived from various Deep Learning techniques to improve usability. Collaborating with the Scrum team to generate working software within a sprint cycle. Writing, developing, evaluating, and documenting new and modified software programs using Test Driven Development ("TDD") methodologies. Building automated systems test environments and simulation software to drive capabilities. Conducting manual tests and preparing software applications for field and customer installation. Supporting end users, including software troubleshooting and training. Researching, investigating, and selecting technical data pertinent to the assigned project. Collaborating with internal teams and external sources to obtain and communicate data relative to engineering requirements. Facilitating software asset management, including maintenance contracts. Preparing and presenting technical reports and recommendations on projects. Telecommuting permitted 2 days per week. Salary: $111,072\- $163,645/year
Experience Required
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Minimum Requirements : Requires a Master’s degree in Computer Engineering, Electrical Engineering or a directly related field plus 1 year of experience as a software engineer or related occupation using machine learning. The 1 year of experience must include 1 year of experience with each of the following: (1\) TensorFlow, PyTorch, or OpenCV; (2\) writing object\-oriented programs in C\+\+ language to support a perception software tech stack used for autonomous agricultural operations; (3\) working with perception related sensor technologies including Camera, Lidar, or Stereo for the use case of automating farm equipment to improve the efficiency of an agronomic operation; (4\) deploying and running software on edge devices with limited CPU processing power and memory capabilities; (5\) applying signal processing techniques for sensor data smoothing and performing data processing and engineering for multimodal datasets; and (6\) conducting field validation under environmental or operational conditions to assess and improve perception software and model performance
CNH Industrial America LLC's ongoing employee referral program does apply to this position.
Interested candidates see all job duties and requirements, and apply online at http://cnh.com/ See Job ID 4181\.
What We Offer
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We offer dynamic career opportunities across an international landscape. As an equal opportunity employer, we are committed to delivering value for all our employees and fostering a culture of respect.
At CNH, we understand that the best solutions come from the diverse experiences and skills of our people. Here, you will be empowered to grow your career, to follow your passion, and help build a better future. To support our employees, we offer regional comprehensive benefits, including:
- *Flexible work arrangements*
- *Savings \& Retirement benefits*
- *Tuition reimbursement*
- *Parental leave*
- *Adoption assistance*
- *Fertility \& Family building support*
- *Employee Assistance Programs*
- *Charitable contribution matching and Volunteer Time Off*
Click here to learn more about our benefits offerings! (US only)
US applicants: CNH Industrial is an equal opportunity employer. This company considers candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Applicants can learn more about their rights by viewing the federal “Know Your Rights” poster here . CNH Industrial participates in E\-Verify and will provide the federal government with your Form I\-9 information to confirm that you are authorized to work in the U.S. You can view additional information here .
Canada applicants: CNH Industrial is an equal opportunity employer. This company considers candidates regardless of race, color, religion, sex, sexual orientation, gender identity, nationality, place of origin, disability, marital status, family status, age, or any other ground prohibited by applicable provincial human rights legislation.
If you need reasonable accommodation with the application process, please contact us at [email protected] .
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Salary Context
This $111K-$163K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At CNH Industrial, 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($137K) sits 24% below the category median. Disclosed range: $111K to $163K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
CNH Industrial AI Hiring
CNH Industrial has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tempe, AZ, US. Compensation range: $163K - $163K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 median, while Prompt Engineer roles sit at $140,000. 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: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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