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Manager Spacex Machine Learning Jobs in Phoenix, AZ

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 ... Maximize GPU utilization through efficient memory management, kernel optimization, and parallel ...

dbi

Alterations Intern

Scottsdale, AZ · On-site

... management process, from learning how and when a product is sold, what happens when it is received ... Gain experience and exposure to hand sewing and machine sewing projects. * Experience the art of ...

dbi

Alterations Intern

Scottsdale, AZ

... management process, from learning how and when a product is sold, what happens when it is received ... Gain experience and exposure to hand sewing and machine sewing projects. * Experience the art of ...

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex ... Familiarity with model governance, model risk management, compliance, or regulatory frameworks is a ...

Shamrock Foods Company

Data Science Analyst

Phoenix, AZ

  • Medical

  • Retirement

  • PTO

The Data Science Analyst is responsible for using data science, machine learning, statistical ... management, and service performance. The Data Science Analyst partners with business leaders ...

Shamrock

Data Science Analyst

Phoenix, AZ · On-site

  • Medical

  • Retirement

  • PTO

The Data Science Analyst is responsible for using data science, machine learning, statistical ... management, and service performance. The Data Science Analyst partners with business leaders ...

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Manager Spacex Machine Learning information

What is the difference between Manager Spacex Machine Learning vs Data Scientist Spacex?

AspectManager Spacex Machine LearningData Scientist Spacex
CredentialsAdvanced degrees in CS, ML, or related fields; leadership experienceDegree in CS, Data Science, or related fields; strong analytical skills
Work EnvironmentTeam leadership, project management, strategic planningData analysis, model development, experimentation
Industry UsageOversees ML teams, manages projects, aligns with business goalsBuilds models, analyzes data, provides insights

The main difference is that the Manager Spacex Machine Learning focuses on leading teams and managing ML projects, while the Data Scientist Spacex primarily develops models and analyzes data to support engineering and business decisions.

What are the most commonly searched types of Spacex Machine Learning jobs in Phoenix, AZ?

The most popular types of Spacex Machine Learning jobs in Phoenix, AZ are:

Manager Spacex Machine Learning jobs near you

Sr. Machine Learning Engineer

Prosum Inc.

Phoenix, AZ • On-site

$130K - $150K/yr

Other

Posted 13 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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