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Ml Inference Jobs in Arizona (NOW HIRING)

We own the compiler that turns high-level models into fast, reliable inference across GPUs powering ... Experience with ML frameworks (e.g.,PyTorch, TensorFlow, JAX) and software stack (e.g.,ONNX,MLIR ...

Lead ML Ops Engineer

Tempe, AZ

$98K - $129K/yr

Oversee enterprisescale AI platforms supporting model training, inference, evaluation, monitoring ... Leadershiplevel expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.

Deliver governed data and features for ML/GenAI (curated datasets, feature pipelines/serving) supporting training and real-time inference, including consistency, caching, backfills, and latency SLOs.

AI Engineer Senior Consultant

Tempe, AZ · Hybrid

$100K - $137K/yr

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). * Implement safety, privacy, and ...

AI Data Engineer - Senior Consultant

Tempe, AZ · Hybrid

$100K - $137K/yr

Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). * Implement safety, privacy, and ...

The ideal candidate will partner closely with AI/ML engineers, data scientists, DevOps teams, and ... inference, and supporting services. Build and manage containerized environments using Docker ...

The ideal candidate will partner closely with AI/ML engineers, data scientists, DevOps teams, and ... inference, and supporting services. Build and manage containerized environments using Docker ...

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Ml Inference information

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Arizona? For Ml Inference jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Ml Inference jobs? Cities in Arizona with the most Ml Inference job openings:
Staff ML Compiler Engineer

Staff ML Compiler Engineer

General Motors

Phoenix, AZ • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


General Motors rating

8.0

Company rating: 8.0 out of 10

Based on 306 frontline employees who took The Breakroom Quiz

6th of 44 rated automakers


Job description

Job Description

About the Mission

GM's vision of Zero Crashes, Zero Emissions, and Zero Congestion guides everything we do in autonomous and assisted driving. The AV organization is building advanced automated driving technologies, including Level 4-capable fully self-driving systems, to move us toward safer, more sustainable, and more accessible mobility.

For the AI Kernels & Compilers team, that mission shows up in the details: turning cutting-edge perception, prediction, and planning research into production-grade software that can run efficiently and reliably on real vehicles at scale. We pioneer new approaches to model export, kernel development, and performance engineering so that every cycle on our accelerators translates into better situational awareness, faster reaction times, and more robust behavior on the road.

If you want your compiler and kernels work to directly influence how automated vehicles understand and react to the world - while operating at the safety, reliability and scale of a company like GM - this is where that impact becomes real.

About the Team

The AI Compiler team sits at the heart of how advanced AI models make it onto the car. We own the compiler that turns high-level models into fast, reliable inference across GPUs powering GM's next-generation autonomous and assisted driving features.

Our work spans graph lowering, operator coverage, kernel integration, and deployment tooling, with a mandate to squeeze every millisecond out of on-vehicle workloads while preserving correctness and robustness in real-world conditions. We partner closely with AI Deployments, AI Solutions, Runtime, and AI Kernels teams to co-design a platform that enables new ideas in research to be quickly and safely shipped to production fleets.

You'll join a group of deep compiler, systems, and GPU engineers who enjoy working on hard problems, diving into MLIR/ONNX and CUDA/TensorRT internals, and mentoring others on performance engineering. We value clear thinking, strong engineering fundamentals, and a culture where people can do the best work of their careers on problems that directly shape the future of automated driving.

The Role

As a Staff Compiler Engineer on the AI Kernels & Compilers team, you will own the end-to-end compilation stack that takes high-level models and turns them into highly optimized inference artifacts running on GM's autonomous and assisted driving platforms. You'll define the technical vision and build the tooling that makes that path fast, reliable, and effortless for ML engineers across the AV organization to compile their models.

You will design and evolve our model export and compilation pipeline-from capturing high-level model graphs, through intermediate representations and compiler transforms, into accelerator-specific inference engines and their integration with our runtime-so that we can simultaneously optimize compilation throughput, model fidelity, and on-vehicle latency. Along the way, you'll build robust tooling to validate numerical correctness, detect and bisect performance regressions, and surface clear, actionable diagnostics back to model authors.

If you want to work at the intersection of compilers, performance engineering, and real-world autonomy , this role puts your decisions directly on the critical path of what runs on the car.

What You'll Do

  • Own and evolve the model compilation toolchain used to deploy large-scaleperception, prediction, and planning models to the AV.

  • Architect new compiler passes and analysis that improve build times, memory footprint, and runtime latency while preserving-or intentionally trading off-fidelity under strict safety and reliability constraints.

  • Collaborate closely with kernels, runtime, and hardware teams to co-design interfaces, shape accelerator capabilities, and ensure the compiler exposes the right abstractions to unlock peak performance on each platform.

  • Set standards and best practices for model export, validation, and debugging so that AV teams can iterate quickly with clear, reproducible performance and accuracy characteristics.

Your Skills & Abilities (Required Qualifications) ****

  • 5+ years of experience in the field of compilers?

  • Experience with ML frameworks (e.g.,PyTorch, TensorFlow, JAX) and software stack (e.g.,ONNX,MLIR, XLA, TVM,TensorRT,etc) ?

  • Expertisein writing production quality Python/C++ code?

  • Expertisein the software development life-cycle - coding, debugging, optimization, testing, integration?

  • BS, or higher degree, in CS/CE/EE, or equivalent?

What Will Give You A Competitive Edge (Preferred Qualifications) ****

  • Experience building andoptimizingONNX-basedmodelexport and deployment pipelines

  • GPU programming (CUDA) and familiarity with ML SW stack (e.g.,cuDNN,cuBLAS)?

  • Experience with ML accelerators and hardware architecture

  • Experience developing and deploying machine learning models?

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

  • The salary range for this role: is $185,100 to $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

#GM-AV-1

This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}.

The selected candidate will be required to travel <25% for this role.

This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources (https://search-careers.gm.com/en/working-at-gm/total-rewards) .

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire (https://search-careers.gm.com/en/how-we-hire) .

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email (Careers.Accommodations@GM.com) us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

We are leading the change to make our world better, safer and more equitable for all through our actions and how we behave. Learn more about:

Our Company (https://search-careers.gm.com/en/working-at-gm/)

Our Culture

How we hire (https://search-careers.gm.com/en/how-we-hire/)

Our diverse team of employees bring their collective passion for engineering, technology and design to deliver on our vision of a world with Zero Crashes, Zero Emissions and Zero Congestion. We are looking for adventure-seekers and imaginative thought leaders to help us transform mobility.

Explore our global locations (https://search-careers.gm.com/en/locations/)

We are determined to lead change for the world through technology, ingenuity and harnessing the creativity of our diverse team. Join us to help lead the change that will make our world better, safer and more equitable for all by becoming a member of GM's Talent Community (beamery.com) (https://flows.beamery.com/generalmotors/talcom) . As a part of our Talent Community, you will receive updates about GM, open roles, career insights and more.

Please note that filling out the form below will not add you to our Talent Community automatically; you will need to use the link above. If you are seeking to apply to a specific role, we encourage you to click "Apply Now" on the job posting of interest.

The policy of General Motors is to extend opportunities to qualified applicants and employees on an equal basis regardless of an individual's age, race, color, sex, religion, national origin, disability, sexual orientation, gender identity/expression or veteran status. Additionally, General Motors is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us at Careers.Accommodations@GM.com .In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.


What General Motors employees say

Pay

Benefits

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Workplace

Get the full story on Breakroom


General Motors logo

About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908