Senior ML Engineer Jobs in Arizona
Senior ML Engineer jobs in Arizona are in strong demand, concentrated in aerospace and defense, semiconductor manufacturing, financial technology, and enterprise software, with openings at every level from mid-career engineer through principal and staff. Phoenix and Scottsdale anchor the majority of hiring, with Tempe emerging as a secondary hub, and established employers like Intel, Raytheon Technologies, and JPMorgan Chase maintain large Arizona engineering teams that regularly recruit senior ml engineers. The most sought-after specialties in the Arizona market are computer vision, natural language processing, and MLOps infrastructure. Find a role that fits below and apply directly.
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Lightningware is looking for a Machine Learning Engineer focused on AI Safety and Moderation to help build the next generation of intelligent safety systems for our live video platform, Thundr and future products.
Thundr operates a real-time video chat service where trust, safety, and moderation are critical to the user experience. We already have moderation systems in production, and we are looking for an engineer who can help us significantly expand their capabilities. Improving detection accuracy, reducing response times, scaling our infrastructure, and researching new ways AI can make real-time online interactions safer.
This role will work across computer vision, multimodal AI, machine learning infrastructure, real-time inference, and applied AI research. You will help develop systems capable of analyzing live video, images, audio, text, and behavioral signals to identify policy-violating or unsafe activity at scale.
You will also play an important role in an upcoming Lightningware project where we are building new moderation technology from the ground up.
This is a highly applied engineering role. We are looking for someone who enjoys taking emerging AI capabilities and turning them into reliable production systems operating at significant scale.
Responsibilities
- Design and build machine learning systems for real-time moderation of live video interactions.
- Develop computer vision and multimodal models capable of detecting unsafe, inappropriate, abusive, or policy-violating content.
- Research and evaluate emerging AI models and techniques that could improve Thundr’s moderation and safety capabilities.
- Improve existing moderation systems by optimizing precision, recall, latency, throughput, and cost.
- Develop systems for model evaluation, benchmarking, dataset creation, labeling, and continuous improvement.
- Build scalable inference infrastructure capable of processing large volumes of real-time user activity.
- Design moderation architectures that intelligently combine automated detection, confidence thresholds, escalation systems, and human review.
- Investigate techniques for detecting adversarial behavior and users attempting to circumvent automated moderation systems.
- Deploy and monitor machine learning models in production environments.
- Develop tools that allow our team to understand model decisions, review incidents, and improve moderation policies.
- Collaborate closely with engineering and leadership teams on new products and safety initiatives.
- Maintain strong documentation around model architecture, evaluation methodology, datasets, deployment systems, and moderation experiments.
Qualifications
- Strong experience building and deploying machine learning or AI systems in production.
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Engineering, or a related technical field, or equivalent practical experience. Master’s degree is a plus, but not required.
- 3+ years of professional experience in machine learning engineering, applied AI, computer vision, or a related field, with experience deploying ML systems into production.
- Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar technologies.
- Experience with computer vision, multimodal AI, NLP, classification systems, or content moderation.
- Understanding of modern deep-learning architectures including transformers and vision models.
- Experience designing model evaluation frameworks and working with metrics such as precision, recall, F1, false-positive rates, and false-negative rates.
- Experience building data pipelines for training, evaluation, and inference.
- Familiarity with cloud infrastructure such as AWS, GCP, or Azure.
- Experience deploying scalable model inference systems through APIs, containers, GPUs, or distributed infrastructure.
- Strong understanding of software engineering principles and the ability to build reliable production systems.
- Ability to independently research new AI techniques, evaluate their usefulness, and turn promising approaches into working prototypes.
Preferred qualifications
- Experience building trust & safety, content moderation, fraud detection, abuse prevention, or platform integrity systems.
- Experience processing live or near-real-time video streams.
- Experience with technologies such as OpenCV, FFmpeg, WebRTC, or video-processing pipelines.
- Experience working with multimodal foundation models or vision-language models.
- Experience with GPU optimization and high-throughput inference.
- Experience designing annotation or labeling pipelines for sensitive datasets.
- Familiarity with model serving technologies such as Triton, ONNX Runtime, TensorRT, Ray, or similar systems.
- Experience with MLOps, model monitoring, experiment tracking, and automated retraining pipelines.
- Experience researching emerging AI techniques and rapidly prototyping new approaches.
What Success Looks Like
In this role, you will help Thundr create moderation systems that can operate intelligently and reliably across millions of real-time interactions.
Success means:
- Detecting harmful content more accurately.
- Reducing false positives that negatively affect legitimate users.
- Identifying unsafe behavior faster.
- Building moderation systems that can scale as Thundr grows.
- Giving our safety teams better tools and signals for making decisions.
- Continuously evaluating emerging AI technology and incorporating meaningful improvements into our platform.
- Establishing reusable AI safety infrastructure that can support both Thundr's existing live service and future products.
Why Lightningware
At Lightningware, you’ll work on real-world AI challenges where your work directly impacts the safety and experience of our users.
You’ll help improve the moderation systems powering Thundr’s live video platform, while researching and implementing new approaches across computer vision, multimodal AI, and real-time moderation.
We also have an upcoming project in development where you’ll have the opportunity to help build its moderation and ML systems from the ground up.
If you’re excited about building practical AI systems, solving difficult real-time problems, and helping shape what we build next, we’d love to hear from you.
Pay: $130,000.00 - $180,000.00 per year
Benefits:
- Dental insurance
- Health insurance
- Paid time off
Ability to Commute:
- Scottsdale, AZ 85260 (Required)
Work Location: In person
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Where Arizona roles are concentrated, by current openings.
Senior ML Engineer Job Market in Arizona
A snapshot from current Arizona openings, updated as new roles post.
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What Arizona Employers Look For
The qualifications that appear most often in senior ML engineer jobs across Arizona.
- Bachelor's or master's degree in computer science, statistics, or a closely related technical field
- Five or more years of hands-on experience designing and deploying production machine learning systems
- Proficiency in Python and at least one major ML framework such as TensorFlow or PyTorch
- Experience with cloud platforms including AWS, Azure, or Google Cloud for model training and serving
- Strong background in MLOps practices including CI/CD pipelines, model monitoring, and data versioning
- Demonstrated ability to mentor junior engineers and lead cross-functional technical projects
Senior ML Engineer Jobs in Arizona: Frequently Asked Questions
How do you become a senior ml engineer in Arizona?
Becoming a senior ml engineer in Arizona typically requires a bachelor's or master's degree in computer science, mathematics, or a related field, followed by several years building and shipping machine learning systems in production environments. Arizona does not require a state-issued license for this role. Candidates who advance quickest often accumulate experience in defense, semiconductor, or fintech environments, which are the dominant hiring sectors in the Phoenix metro, and build a portfolio of deployed model work.
How much do senior ML engineers make in Arizona?
Senior ML engineers in Arizona earn a median of about $105,240 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $52,450 for the lowest 10% to over $166,870 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior ml engineers in Arizona?
Employers hiring senior ml engineers in Arizona right now include Optum, CVS Health, and Thundr, based on current listings on Migrate Mate as of September 2026. Arizona's concentration of aerospace primes, chip manufacturers, and large financial institutions means demand stays consistent across economic cycles, giving senior candidates a broad range of industry contexts to choose from.
Which Arizona cities have the most senior ml engineer jobs?
Phoenix, Tempe, and Gilbert account for the largest share of senior ml engineer openings in Arizona. Phoenix drives the most volume as home to the state's largest tech corridors and corporate campuses, Scottsdale attracts fintech and enterprise software firms, and Tempe benefits from its proximity to Arizona State University and the startup and R&D operations that cluster around it.
Are there remote senior ml engineer jobs in Arizona?
Yes, and more than most fields. About 0% of senior ml engineer openings tied to Arizona are remote or hybrid as of September 2026, reflecting the fact that most of the work happens in code, notebooks, and cloud infrastructure rather than on a physical site. Research, modeling, and experimentation phases tend to be the most remote-friendly, while roles that require close collaboration with hardware or defense-cleared facilities are more likely to require an on-site presence.
How can I get hired as a senior ml engineer in Arizona with little or no experience?
The most realistic entry path is targeting associate or junior machine learning engineer roles at Arizona's large defense and semiconductor employers, which run structured new-graduate programs, including Intel's university hiring pipeline and Raytheon's engineering development program, where candidates transition into ML-adjacent data science or software engineering positions before moving into dedicated ML work. Building a public portfolio of end-to-end projects, contributing to open-source ML tooling, and completing cloud certifications from AWS or Google Cloud gives candidates a concrete edge when competing for those early-career openings.
Where can I find and apply to senior ml engineer jobs in Arizona?
You can find and apply to senior ml engineer jobs in Arizona on Migrate Mate, which lists current openings tied to the Arizona market. Search the available roles, identify the ones that match your background and preferred location, and apply directly to each one that fits.
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