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Afternoon Mechanical Engineering Machine Learning Jobs

... Mechanical Engineering, Control Engineering, Machine Learning, Statistics, or a related field - Passionate about self-driving vehicles and real-world robotics solutions. - Experience collecting ...

... engineering to design, build, and maintain systems for high-performance, large-scale knowledge discovery in financial data. Machine learning developers have the opportunity to be part of an inclusive ...

A blend of data engineering, machine learning, and product innovation skills that let you jump into a fast-paced environment and contribute on day one * Familiar with monitoring, deployment tools ...

Description In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning ...

Machine Learning FEA Engineer

Bodega Bay, CA · On-site

$139.50K - $258.10K/yr

D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline Publications in top journals or conferences Minimum Qualifications Strong Expertise in Machine Learning, Deep ...

Machine Learning FEA Engineer

Bodega Bay, CA · On-site

$139.50K - $258.10K/yr

D. in Computer Science, Machine Learning, Mechanical Engineering, or a similar discipline Publications in top journals or conferences Minimum Qualifications Strong Expertise in Machine Learning, Deep ...

In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and ...

Machine Learning FEA Engineer

San Francisco, CA · On-site

$147.40K - $272.10K/yr

S. in computer science, machine learning, mechanical engineering, or a similar discipline along with 3+ years of relevant experience Preferred Qualifications * Strong expertise in GNNs, CNNs, and ...

Machine Learning FEA Engineer

Culver City, CA · On-site

$147.40K - $272.10K/yr

S. in computer science, machine learning, mechanical engineering, or a similar discipline along with 3+ years of relevant experience Preferred Qualifications * Strong expertise in GNNs, CNNs, and ...

Machine Learning And Artificial Intelligence Developer You will be responsible for Machine Learning ... Mechanical Engineering. Benefits of Working with Our Clients * E-Verified. * Filing of H1b and ...

Machine Learning Engineer

Centreville, VA · On-site

$102K - $144.38K/yr

Machine Learning Engineer II The Machine Learning Engineer II will be a member of the Learning and ... Engineering, Aerospace, or Mechanical Engineering * Minimum of 2 - 5 years' experience, and 2+ ...

New

Machine Learning Engineer Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software ... S. or Ph.D in engineering, math, computer science, or related field * Excellent technical ...

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Afternoon Mechanical Engineering Machine Learning information

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How much do afternoon mechanical engineering machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for afternoon mechanical engineering machine learning in the United States is $102,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,500.00 and $126,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Afternoon Mechanical Engineering Machine Learning professional, and why are they important?

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 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 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.

More about Afternoon Mechanical Engineering Machine Learning jobs
What cities are hiring for Afternoon Mechanical Engineering Machine Learning jobs? Cities with the most Afternoon Mechanical Engineering Machine Learning job openings:
What are the most commonly searched types of Mechanical Engineering Machine Learning jobs? The most popular types of Mechanical Engineering Machine Learning jobs are:
What states have the most Afternoon Mechanical Engineering Machine Learning jobs? States with the most job openings for Afternoon Mechanical Engineering Machine Learning jobs include:
Research Scientist - Machine Learning

Research Scientist - Machine Learning

ISEE

Remote

Full-time

Posted 23 days ago


Job description

ISEE is seeking full-time Research Scientists to join our team. The ideal candidate has several years of research/work experience.
Role responsibilities include:
- Leading research contributing to the development of humanistic AI for autonomous systems
- Conducting research in the areas of: Robotics, Artificial Intelligence, Machine Learning, Perception, Modeling, Simulation, Applied Mathematics, Probabilistic Modeling and Inference or related areas
- Collaborating with engineering and business teams to develop novel solutions to real-world problems
- Designing experiments and metrics for benchmarking resultsPublishing research in top-tier conferences and journals
Qualifications:
- PhD in Robotics, Computer Science, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Control Engineering, Machine Learning, Statistics, or a related field
- Passionate about self-driving vehicles and real-world robotics solutions.
- Experience collecting, processing, and analyzing real-world data.
- Strong presentation and communication skills.
Recommended
- Publication record in top-tier conferences in Robotics and related fields.
- Programming experience, ideally with Python and/or C++.
- Robotics experience is a plus.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.