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Senior Staff Machine Learning Engineer Jobs in Arizona

Prosum Inc.

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

Sr. Machine Learning Engineer Salary Range: $130k to $150k Our client is seeking a Sr. Machine Learning Engineering for a direct hire role to sit in North Phoenix, AZ or Hillsboro, OR. This role will ...

Intel

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research and model fine tuning. This role sits at the intersection of research and engineering: the ideal ...

MY DR NOW

AI & Machine Learning Engineer

Chandler, AZ · On-site

$100K - $110K/yr

Knowledge of Machine Learning and Generative AI frameworks * Strong engineering fundamentals and problem-solving skills * A builder mindset -- curious, resourceful, fast-moving, and focused on ...

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Senior Staff Machine Learning Engineer information

What does a senior staff machine learning engineer do?

A Senior Staff Machine Learning Engineer leads the design, development, and deployment of complex machine learning systems within an organization. They work closely with cross-functional teams to identify business challenges that can be addressed with machine learning and guide the technical strategy for implementing solutions. Their responsibilities often include mentoring junior engineers, setting best practices, overseeing large-scale projects, and ensuring models are robust, scalable, and ethically implemented. Additionally, they may contribute to research and development, staying up-to-date with the latest advancements in the field.

What are the primary challenges a senior staff machine learning engineer faces when leading large-scale ML projects?

Senior Staff Machine Learning Engineers often navigate complex challenges such as aligning cross-functional teams, ensuring model scalability, and maintaining data integrity across evolving pipelines. They are responsible for setting technical direction, mentoring junior engineers, and driving collaboration between data scientists, software engineers, and product managers. Balancing hands-on technical work with high-level architectural decisions, while also keeping up with rapid advancements in the field, is key to success in this role.

What are the key skills and qualifications needed to thrive as a senior staff machine learning engineer, and why are they important?

To thrive as a Senior Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, software engineering, and a relevant advanced degree (often MS or PhD). Mastery of tools such as Python, TensorFlow, PyTorch, distributed computing frameworks, and experience with cloud platforms is typically required. Strong leadership, communication, and project management skills distinguish top performers in this role. These abilities are crucial for designing scalable ML solutions, leading teams, and driving impactful business outcomes.

What is the difference between Senior Staff Machine Learning Engineer vs Machine Learning Engineer?

AspectSenior Staff Machine Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's/PhD in CS, AI, or related; experience in ML frameworksBachelor's/Master's in CS, AI, or related; some experience in ML
Work EnvironmentLeadership roles, cross-team collaboration, strategic planningImplementation, model development, experimentation
Industry UsageTech companies, research labs, large enterprisesStartups, tech firms, research projects

The Senior Staff Machine Learning Engineer typically holds a more senior, strategic role with leadership responsibilities, while the Machine Learning Engineer focuses on developing and deploying ML models. Both roles require strong technical skills, but the senior position involves guiding projects and mentoring teams.

What are popular job titles related to Senior Staff Machine Learning Engineer jobs in Arizona?

For Senior Staff Machine Learning Engineer jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Senior Staff Machine Learning Engineer jobs in Arizona look for?

The top searched job categories for Senior Staff Machine Learning Engineer jobs in Arizona are:

What cities in Arizona are hiring for Senior Staff Machine Learning Engineer jobs?

Cities in Arizona with the most Senior Staff Machine Learning Engineer job openings:

Senior Staff Machine Learning Engineer jobs near you

Sr. Machine Learning Engineer

Phoenix, AZ • On-site

Prosum Inc.
Recruiting and Staffing Services • 201 - 500 employees
Learn more about Prosum Inc.external

$130K - $150K/yr

Other

Posted 21 days ago

Job description

Job Description
Sr. Machine Learning Engineer
Salary Range: $130k to $150k
Our client is seeking a Sr. Machine Learning Engineering for a direct hire role to sit in North Phoenix, AZ or Hillsboro, OR. This role will be onsite 4 days a week and 1 remote day.
JOB SUMMARY
The role of Senior Machine Learning Engineer will architect and optimize real-time, high-throughput, and ultra-low latency image pipelines for next-generation Mask Inspection Tools. Responsibilities include eliminating hardware bottlenecks through CUDA kernel tuning and GPU parallel computing, ensuring deep learning models and CV algorithms seamlessly processing massive, high-bandwidth streaming data at production scale.
ESSENTIAL DUTIES AND RESPONSIBILITIES
High-Performance Computing Pipeline Architecture
  • Design, implement, and optimize high-throughput, low-latency image processing pipelines for real-time optical inspection and machine vision systems.
  • Develop scalable architectures capable of processing large volumes of imaging data while meeting stringent latency and reliability requirements.
  • Profile and optimize system performance across CPU, GPU, memory, and I/O subsystems.
GPU Acceleration
  • Design, develop, and optimize CUDA kernels to accelerate deep learning inference and classical computer vision algorithms.
  • Maximize GPU utilization through efficient memory management, kernel optimization, and parallel programming techniques.
  • Evaluate and implement performance improvements using NVIDIA GPU technologies and profiling tools.
Model Deployment & Optimization
  • Optimize, quantize, and deploy machine learning models using TensorRT, ONNX Runtime, or similar inference frameworks.
  • Integrate AI models into production-grade C++ and Python applications.
  • Improve inference throughput, latency, and resource utilization while maintaining model accuracy.
  • Develop automated deployment and validation pipelines for machine learning models.
Concurrency & Systems Optimization
  • Architect and implement multi-threaded, high-concurrency software components for data acquisition, buffering, streaming, and real-time processing.
  • Design robust synchronization and communication mechanisms between hardware interfaces and AI processing pipelines.
  • Optimize end-to-end system performance for deterministic, real-time execution.
Cross-Functional Collaboration
  • Partner with machine learning scientists, computer vision engineers, hardware engineers, and software developers to deliver integrated AI solutions.

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