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Ml Inference Jobs in Arizona (NOW HIRING)

Entertainment Partners

AI Engineer

Tempe, AZ · On-site

Experience serving ML models at scale using Triton Inference Server, TorchServe, Ray Serve, or similar. * Contributions to open-source ML projects or published research (papers, patents, or technical ...

New

Entertainment Partners

AI Engineer

Tempe, AZ

Experience serving ML models at scale using Triton Inference Server, TorchServe, Ray Serve, or similar. * Contributions to open-source ML projects or published research (papers, patents, or technical ...

New

LPL Financial

Sr. Analyst, Data Science

Tempe, AZ · On-site

$85K - $143K/yr

Stay current on advances in applied ML and bring emerging methods to bear on relevant business problems. Causal Inference & Experimentation * Design and analyze A/B tests and observational studies to ...

Master Electronics

Data Scientist II

Phoenix, AZ

... inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible * Translate business problems into ML ...

Master Electronics

Data Scientist II

Phoenix, AZ

... inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible * Translate business problems into ML ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

... inference techniques (uplift modeling, difference-in-differences, synthetic controls, instrumental variables) where randomized experiments aren't feasible * Translate business problems into ML ...

Tata Consultancy Service Limited

AI Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

Design, develop, and deploy scalable AI/ML and GenAI solutions to solve complex business problems ... inference, and model gateways • Evaluation, observability, and safety tooling for autonomous ...

Waabi

Senior Software Engineer, Auto Labelling

Phoenix, AZ · On-site +1

$170K - $220K/yr

... with ML researchers and engineers to seamlessly deploy new architectures into the production ... online inference. - Proficient in Python with a track record of writing high-quality, well ...

Waabi

Senior Software Engineer, Auto Labelling

Phoenix, AZ · On-site +1

$170K - $220K/yr

... with ML researchers and engineers to seamlessly deploy new architectures into the production ... online inference. - Proficient in Python with a track record of writing high-quality, well ...

Axon

Senior Machine Learning Scientist

Scottsdale, AZ

$92K - $125K/yr

Design and implement efficient and scalable MLLM models for inference and analysis of multimodal ... PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML ...

Axon

Senior Machine Learning Scientist

Scottsdale, AZ · On-site

$92K - $125K/yr

Design and implement efficient and scalable MLLM models for inference and analysis of multimodal ... PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML ...

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Ml Inference information

What is a $900000 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 involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.

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.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.

Which 3 jobs will survive AI?

Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.

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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.

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 job categories do people searching Ml Inference jobs in Arizona look for? The top searched job categories for Ml Inference jobs in Arizona are:
What cities in Arizona are hiring for Ml Inference jobs? Cities in Arizona with the most Ml Inference job openings:
Ml Inference jobs near you
Sr. Engineer, Machine Learning Operations

Sr. Engineer, Machine Learning Operations

Exact Sciences

Phoenix, AZ • On-site

$209K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Exact Sciences rating

8.5

Company rating: 8.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

21st of 105 rated laboratories

Job description

Help us change lives
At Exact Sciences, we're helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you're working to help others.
Position Overview
The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with cross-functional partners-including biostatisticians, bioinformatics scientists, AI scientists, and software engineers-to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications. The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle-from data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying in-depth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable, and aligned with the company's mission to help eradicate cancer.
Essential Duties
Include, but are not limited to, the following:
  • Designs, implements, and maintains end-to-end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real-time inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production-grade services integrated into customer-facing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the company's Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications
  • Bachelor's Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time.

Preferred Qualifications
  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.

#LI-CB1
Salary Range:
National Ranges: $ 123,000.00 - $209,000.00
California Ranges: $152,000.00- $228,000.00
The annual base salary shown is a national range for this position on a full-time basis and may differ by hiring location. In addition, this position is bonus eligible.
Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.
Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.
Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.
We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.
To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.

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