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Mechanical Engineering Machine Learning Jobs (NOW HIRING)

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

Driving engineering best practices across CI/CD, observability, testing, and automation Tech stack ... Machine Learning Engineering ✔ MLOps Engineering ✔ Platform Engineering ✔ Software ...

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Experience in data analysis, data engineering, and machine learning data operations. Experience designing data quality control processes, data curation workflows, or Human-in-the-Loop initiatives.

Apple

Machine Learning Engineer - LLM

Cupertino, CA · On-site

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

Apple

AIML - Staff Machine Learning Engineer

Cary, NC · On-site

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

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Mechanical Engineering Machine Learning information

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$45.5K

$102.9K

$166.5K

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

As of Jul 5, 2026, the average yearly pay for 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 you make $200,000 a year as a mechanical engineer?

Mechanical engineers can earn $200,000 or more annually, typically in senior roles, specialized fields, or with extensive experience and advanced skills such as CAD software, project management, or certifications. High salaries are often found in industries like aerospace, energy, or in managerial positions, especially in regions with a high cost of living or demand for engineering expertise.

What is a Mechanical Engineering Machine Learning job?

A Mechanical Engineering Machine Learning job involves applying machine learning techniques to solve mechanical engineering problems. This can include optimizing designs, predicting failures, automating processes, and improving system efficiency. Engineers in this field use data-driven models, simulations, and sensor data to enhance mechanical systems. The role requires knowledge of both mechanical engineering principles and machine learning algorithms.

What engineers make $500,000?

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

What are the key skills and qualifications needed to thrive in the Mechanical Engineering Machine Learning position, and why are they important?

To thrive in a Mechanical Engineering Machine Learning role, you need a solid background in mechanical engineering principles and practical experience with machine learning algorithms, supported by a degree in mechanical engineering, computer science, or a related field. Proficiency in Python, MATLAB, CAD software, and machine learning libraries like TensorFlow or scikit-learn is highly valued, as are certifications in data science or AI. Analytical thinking, problem-solving, and effective collaboration are essential soft skills, helping you bridge mechanical systems and data-driven modeling. These skills enable innovative solutions for design, analysis, and automation in multidisciplinary engineering environments.

What engineers make $300,000 a year?

Senior mechanical engineers with extensive experience, specialized skills, and advanced certifications can earn $300,000 or more annually, especially in high-demand industries like aerospace, automotive, or energy. Roles involving leadership, project management, or working in competitive markets tend to offer higher compensation.

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 data science and AI tools, can facilitate their transition into machine learning roles. Interdisciplinary expertise enhances their ability to solve complex engineering problems using machine learning techniques.

What are typical projects or challenges faced by Mechanical Engineering Machine Learning professionals?

Mechanical Engineering Machine Learning professionals often work on projects involving predictive maintenance of mechanical systems, optimization of manufacturing processes, or the integration of smart sensors and IoT devices in industrial applications. A common challenge is translating mechanical data into meaningful inputs for machine learning models, requiring close collaboration with domain experts and software engineers. You may also tackle tasks like automating design processes, simulating complex systems, or developing algorithms for fault detection. These projects typically involve both independent problem-solving and team-based collaborations, making adaptability and communication critical to success.

More about Mechanical Engineering Machine Learning jobs
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 Mechanical Engineering Machine Learning jobs? States with the most job openings for Mechanical Engineering Machine Learning jobs include:
What job categories do people searching Mechanical Engineering Machine Learning jobs look for? The top searched job categories for Mechanical Engineering Machine Learning jobs are:
Mechanical Engineering Machine Learning jobs near you
Infographic showing various Mechanical Engineering Machine Learning job openings in the United States as of June 2026, with employment types broken down into 69% Full Time, 27% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $102,878 per year, or $49.5 per hour.
Senior Data Science and Machine Learning Engineer

Senior Data Science and Machine Learning Engineer

1 point system

New York, NY • Remote

Contractor

Posted 23 days ago

Job description

Job Summary:

  • We are seeking a Senior Data Science Engineer to design, build, and scale data-driven systems that power advanced analytics and machine learning across our organization. This role sits at the intersection of software engineering and data science; you’ll be responsible for building robust data pipelines, enabling experimentation, and deploying production-ready machine learning models.
  • As a senior team member, you will mentor junior engineers and data scientists, influence architectural decisions, and help shape the long-term AI and data strategy.

Key Responsibilities:

  • Develop, deploy, and maintain machine learning models in production environments.
  • Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
  • Ensure high-quality data through monitoring, validation, and robust testing frameworks.
  • Architect and maintain data platforms and tools for experimentation, model serving, and feature engineering.
  • Explore and integrate Large Language Models (LLMs) and other generative AI approaches into business applications and data workflows.
  • Contribute to code reviews, technical design discussions, and best practices for the team.
  • Mentor and guide junior engineers/data scientists, fostering technical excellence and career growth.
  • Stay current with emerging technologies in Data Science, Machine Learning, LLM Ops, ML Ops.

Education Requirement:

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • Master’s degree or PhD is a strong plus.

Experience:

  • 5+ years of experience in data engineering, machine learning engineering, or related roles.
  • Strong proficiency in Python (Pandas, NumPy, PySpark, or similar).
  • Solid understanding of ML model development, training, and deployment pipelines.
  • Experience with ML model monitoring and observability frameworks.
  • Experience with deep learning frameworks(TensorFlow, PyTorch).
  • Familiarity with CI/CD, version control (Git),and modern ML Ops practices.