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Afternoon Mechanical Engineering Machine Learning Jobs

Willing Tech

Machine Learning Engineer

San Francisco, CA · On-site +1

$172K - $384K/yr

Develop machine learning systems that generate structured vector graphics (e.g., SVG/JSON ) from ... Job functionAnalyst, Consulting, and Engineering * IndustriesSoftware Development, Biotechnology ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

Collaborate with the engineering team to integrate machine learning solutions into projects. Stay updated on the latest machine learning technologies and trends. Develop and implement quantum machine ...

Apple

Machine Learning Engineer- GenAI

Cupertino, CA · On-site

Masters in Artificial intelligence, Machine Learning, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field. Preferred ...

Atomic Machines

Mechanical Engineer

Santa Clara, CA · On-site

The Mechanical Engineering team is at the forefront of designing and developing state-of-the-art ... Drive your work through rapid learning loops leveraging our in-house Lab, Fab, and Machine Shop.

Atomic Machines

Mechanical Engineer

Emeryville, CA · On-site

The Mechanical Engineering team is at the forefront of designing and developing state-of-the-art ... Drive your work through rapid learning loops leveraging our in-house Lab, Fab, and Machine Shop.

1 point system

AI Engineer - Machine Learning 3

Redmond, WA · Remote

$117K - $140K/yr

... engineering or related field required Summary: • As a Machine Learning Data Scientist, you will collaborate closely with researchers, engineers, designers, and product partners to evaluate emerging ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Bachelors in Computer Science, Electrical Engineering, Mechanical Engineering (or similar ...

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All JobsAfternoon Mechanical Engineering Machine Learning Jobs

Afternoon Mechanical Engineering Machine Learning information

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$45.5K

$102.9K

$166.5K

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

As of Jul 14, 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.

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 for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding of data science tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise and additional training in machine learning techniques are often required for such positions.

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.

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.

Will MLE be replaced by AI?

In the context of an Afternoon Mechanical Engineering Machine Learning role, MLE (Machine Learning Engineer) involves designing and deploying models that often complement AI systems. While AI automation can handle certain tasks, MLE professionals are essential for developing, optimizing, and maintaining machine learning solutions, making complete replacement unlikely in the near term. Skills in programming, data analysis, and understanding of algorithms remain critical for MLE roles.

What engineer makes $500,000 a year?

Senior mechanical engineers with extensive experience, specialized skills in machine learning, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large corporations. Achieving this level often requires advanced degrees, certifications, and a strong track record of project success and innovation.

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.

Can you make $200,000 a year as a mechanical engineer?

Achieving a $200,000 annual salary as a mechanical engineer is possible but typically requires extensive experience, advanced skills in areas like machine learning or automation, and often positions in management or specialized industries such as aerospace or energy. Salaries vary based on location, company size, and individual expertise, with top earners often holding senior or lead roles and possessing professional certifications.

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.
More about Afternoon Mechanical Engineering Machine Learning jobs
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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:
Afternoon Mechanical Engineering Machine Learning jobs near you

Machine Learning / Reinforcement Learning Infrastructure Engineer

Eka Robotics

Cambridge, MA • On-site

$118K - $155K/yr

Full-time

Posted 11 days ago

Job description

Job Summary:
Eka Robotics is on a mission to build intelligence for the physical world through advanced robotics. They are seeking a Reinforcement/Machine Learning Infrastructure Engineer to design, implement, and maintain large-scale model training systems that will enhance their robotics research and deployment efforts.
Responsibilities:
• Own Training Infrastructure: Design, implement, and maintain robust systems for large-scale model training, including job orchestration, scheduling, checkpointing, and experiment tracking.
• Developer Experience & Tooling: Build streamlined, intuitive abstractions for launching, monitoring, debugging, and reproducing experiments, minimizing friction and maximizing productivity for our research teams.
• Scale Distributed Training: Work closely with researchers to reliably scale reinforcement learning and machine learning pipelines across compute clusters.
• Resource Management: Ensure efficient allocation and utilization of cloud-based compute resources while building the foundational systems needed for future scaling.
• Collaborate with Researchers: Partner with the research team to understand their needs, build infrastructure that supports cutting-edge methods, guide best practices for training at scale, and contribute to core JAX model and training code.
Qualifications:
Required:
• BS, MS or higher in Computer Science, Computer Engineering, Machine Learning or a related technical field.
• Strong software engineering fundamentals with a proven track record of building ML training infrastructure, internal developer platforms, or scalable systems.
• Hands-on experience with large-scale training using JAX (preferred), PyTorch, or TensorFlow.
• Familiarity with distributed training, multi-host setups, data pipelines, and managing workloads on cloud platforms or orchestration systems (e.g., Kubernetes, SLURM, GCP, AWS).
• Strong cross-functional communication skills, a deep ownership mindset, and a passion for building tools that improve the developer experience.
• Experience building automated testing pipelines, CI/CD for ML workflows, and custom logging/telemetry stacks.
Preferred:
• Background in robotics, reinforcement learning or other machine learning systems.
• Experience designing abstractions that balance researcher flexibility with system reliability.
Company:
Founded in , the company is headquartered in Cambridge, MA, US, , with a team of 11-50 employees. The company is currently Early Stage.

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