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Afternoon Mechanical Engineering Machine Learning Jobs in Arizona

Prosum Inc.

Sr. Machine Learning Engineer

Phoenix, AZ · On-site

$130K - $150K/yr

... Machine Learning Engineering for a direct hire role to sit in North Phoenix, AZ or Hillsboro, OR ... Design robust synchronization and communication mechanisms between hardware interfaces and AI ...

Varsity Tutors

Mechanical Engineering Tutor

Tucson, AZ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

Varsity Tutors

Mechanical Engineering Tutor

Mesa, AZ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

Varsity Tutors

Mechanical Engineering Tutor

Tempe, AZ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

Varsity Tutors

Mechanical Engineering Tutor

Gilbert, AZ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

Varsity Tutors

Mechanical Engineering Tutor

Phoenix, AZ · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

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Afternoon Mechanical Engineering Machine Learning information

What is an afternoon mechanical engineering machine learning job?

An Afternoon Mechanical Engineering Machine Learning job typically refers to a position where professionals apply machine learning techniques to solve problems in mechanical engineering, with working hours scheduled in the afternoon. These roles often involve analyzing engineering data, developing predictive models, and optimizing mechanical systems using advanced algorithms. The work may include tasks such as fault detection, predictive maintenance, or process optimization, leveraging both engineering expertise and machine learning skills. Employees in such positions usually have backgrounds in both mechanical engineering and computer science or data analytics.

What are the key skills and qualifications needed to thrive as an afternoon mechanical engineering machine learning professional?

To excel in this role, you need a solid background in mechanical engineering principles, mathematics, and machine learning concepts, usually supported by a relevant engineering degree. Familiarity with technical tools such as Python, MATLAB, CAD software, and machine learning frameworks (like TensorFlow or scikit-learn) is typically required. Strong analytical thinking, problem-solving, and effective teamwork are valuable soft skills for integrating machine learning with mechanical systems. These competencies are crucial for developing innovative solutions and optimizing engineering processes with data-driven approaches.

How do mechanical engineers specializing in machine learning typically collaborate with other departments during afternoon shifts?

Mechanical engineers working in machine learning often collaborate closely with data scientists, software developers, and production teams, especially during afternoon shifts when testing and implementation often ramp up. They may participate in cross-functional meetings to align on project goals, troubleshoot issues with live data, and refine machine learning models based on feedback from manufacturing or operations staff. This collaborative environment helps ensure that algorithms are practical, efficient, and aligned with real-world applications. Effective communication and adaptability are key, as priorities can shift rapidly based on production needs.

What is the difference between Afternoon Mechanical Engineering Machine Learning vs Afternoon Mechanical Engineering Data Analysis?

AspectAfternoon Mechanical Engineering Machine LearningAfternoon Mechanical Engineering Data Analysis
Required CredentialsBachelor's or Master's in Mechanical Engineering, proficiency in machine learning toolsBachelor's or Master's in Mechanical Engineering, strong data analysis skills
Work EnvironmentResearch labs, tech companies, manufacturing firmsDesign firms, manufacturing plants, research institutions
Employer & Industry UsageTech-driven engineering sectors applying AI/MLTraditional engineering sectors focusing on data interpretation
Search & Comparison IntentUnderstanding roles involving AI/ML in mechanical engineeringComparing data analysis tasks within mechanical engineering

Afternoon Mechanical Engineering Machine Learning focuses on applying AI and machine learning techniques to mechanical engineering problems, often requiring programming and data modeling skills. In contrast, Afternoon Mechanical Engineering Data Analysis emphasizes interpreting and visualizing data to inform engineering decisions. Both roles share foundational engineering knowledge but differ in their technical focus and application areas.

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms and models for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required.
Afternoon Mechanical Engineering Machine Learning jobs near you

Senior Machine Learning Engineer I

Tucson, AZ • On-site

Rocket Lab Corporation
Aerospace Product and Parts Manufacturing • 201 - 500 employees

9.2

Company rating: 9.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

4th of 72 rated aerospace companies

People enjoy working here

Good employer

Paid breaks

Learn more about Rocket Lab Corporationexternal

$115K - $152K/yr

Full-time

Posted 5 days ago

Job description

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets - we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space - our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

SENIOR MACHINE LEARNING ENGINEER I

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer I based at our Optical Systems sites in Tucson, AZ, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

WHAT YOU'LL DO

  • Contribute your experience to developing solutions for real-world problems.
  • Design, train, and deploy machine learning models for Optical Systems applications
  • Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
  • Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
  • Preform rapid prototyping and enhanced development to be integrated into operational systems.
  • Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
  • Stay current with ML research and evaluate new tools, frameworks, and techniques

 WHAT WE'RE LOOKING FOR IN A SENIOR MACHINE LEARNING ENGINEER I:

  • Bachelor's degree and 5+ years of experience, master's degree and 3+ years of experience, or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
  • Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
  • Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
  • Strong math background, particularly linear algebra
  • Proficiency in Python
  • Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
  • Software engineering fundamentals: version control, testing, CI/CD, containerization
  • S. citizenship is required, due to program requirements
  • Ability to obtain and maintain an U.S. Government Security Clearance

NICE TO HAVE: 

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

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