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Freelance Full Stack Machine Learning Engineer Jobs in Arizona

Prosum Inc.

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 ...

Rocket Lab Corporation

Machine Learning Engineer II

Tucson, AZ · On-site

$92K - $126K/yr

MACHINE LEARNING ENGINEER II Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense ...

Bespoke Labs

Machine Learning Engineer

Chandler, AZ

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Phoenix, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Flagstaff, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Chandler, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Tucson, AZ

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Mesa, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Glendale, AZ

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Phoenix, AZ

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Glendale, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Tucson, AZ · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Mesa, AZ

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

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Freelance Full Stack Machine Learning Engineer information

What is the difference between Freelance Full Stack Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Full Stack Machine Learning EngineerFreelance Data Scientist
CredentialsProficiency in programming, machine learning, and full stack developmentStrong statistical, analytical, and programming skills, often with data analysis certifications
Work EnvironmentDevelops and deploys ML models, works on both front-end and back-end systemsAnalyzes data, builds models, and provides insights, mainly focusing on data analysis
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, reporting, and predictive modeling

Freelance Full Stack Machine Learning Engineers focus on building and deploying machine learning models within full stack applications, combining software development with ML expertise. Freelance Data Scientists primarily analyze data and create models for insights. While both roles require programming skills, the engineer's role emphasizes deployment and integration, whereas the data scientist's role centers on analysis and interpretation.

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Freelance Full Stack Machine Learning Engineer jobs near you

Machine Learning Engineer

Prosum Inc.

Phoenix, AZ • On-site

$130K - $150K/yr

Other

Re-posted yesterday

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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