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Mechanical Engineering Machine Learning Jobs (NOW HIRING)

Atomic Machines

Mechanical Engineer

Santa Clara, CA

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.

SynergisticIT

Machine Learning Engineer

Boston, MA · On-site

Work with an international top-notch engineering team with full commitment on Machine Learning ... Mechanical Engineering. Benefits of Working with Our Clients * E-Verified. * Long Term Positions

Atomic Machines

Mechanical Engineer

Emeryville, CA

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.

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$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 ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$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 ...

Hadrian

Machine Learning Engineer

Los Angeles, CA

$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 ...

Apple

Machine Learning Engineer - LLM

Cupertino, CA · On-site

$147K - $220K/yr

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

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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 Jun 15, 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.

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, 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 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 leadership roles can earn $300,000 or more annually, especially in high-demand industries like aerospace, automotive, or energy. Achieving this level often requires advanced degrees, professional certifications, and a track record of significant project contributions.

Which 5 jobs will survive AI?

Mechanical engineering roles that involve designing, maintaining, and improving machinery are likely to persist as they require complex problem-solving and hands-on expertise. Jobs that focus on creative innovation, systems integration, and specialized technical skills, such as robotics engineers and systems analysts, are also expected to remain in demand despite advances in AI. Continuous learning and certification in relevant tools like CAD software and automation systems can enhance job security in these fields.

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 relevant certifications can enhance their effectiveness in this field.

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
Machine Learning Engineer

Machine Learning Engineer

Darwill, Inc.

Oakbrook Terrace, IL • Hybrid

Other

Posted 25 days ago

Job description

Description

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING)


Overview

Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.


We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.


This role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role..

Location

Chicago, IL area (Oak Brook / West Suburbs)
Hybrid work model with 1-2 days onsite per week required

Reports To

VP of Data Engineering & Data Science

Responsibilities / Essential Functions

Data Engineering & Platform Foundations

  • Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake
  • Independently implement data transformations, joins, and aggregations across large, multi-source datasets
  • Build and maintain data validation and quality checks to ensure reliability of  downstream analytics and ML workflows
  • Optimize Databricks jobs for performance, scalability, and cost efficiency
  • Write and maintain clear technical documentation for data pipelines and tables

ML Engineering & MLOps

  • Partner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment
  • Productionize propensity, ranking, and segmentation models used in large-scale marketing  campaigns
  • Build and maintain repeatable ML pipelines for training, batch scoring, and inference
  • Implement model versioning, experiment tracking, and reproducibility standards
  • Support  model performance monitoring, drift detection, and retraining cycles

Deployment, Monitoring & Operations

  • Deploy data pipelines and ML workflows into production environments serving      millions of records
  • Implement monitoring and alerting for data and ML pipelines
  • Support  A/B testing and model performance evaluation in partnership with Data      Science
  • Troubleshoot production issues independently and collaborate effectively when      escalation is needed

GenAI (Secondary / Directional)

  • Contribute to GenAI initiatives as capacity allows
  • Stay informed on emerging AI technologies and tooling
    (GenAI is not the primary focus of this role today.)

Required Qualifications

Experience

  • 3-6  years of professional experience in machine learning engineering, data      engineering, or a closely related role
  • Experience  working in production environments with minimal day-to-day supervision
  • Demonstrated ability to collaborate effectively with Data Scientists and translate      models into production systems

Technical Skills (Must-Have)

Data Engineering & Platform

  • Apache  Spark (PySpark, SparkSQL)
  • Databricks  (ETL pipelines, workflows, Delta Lake)
  • Strong SQL skills (complex queries, joins, window functions, optimization)
  • Experience building and maintaining scalable data pipelines

Programming & Machine Learning

  • Python  (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)
  • Feature engineering and data preparation for ML models
  • Working knowledge of supervised learning models (classification, regression, ranking)

MLOps & Production

  • Experience  deploying ML models into production
  • Model versioning and experiment tracking (e.g., MLflow or similar)
  • Monitoring data quality and model performance in production
  • Supporting retraining and validation workflows

Cloud & Tooling

  • Experience  with a major cloud platform (Databrick, AWS)
  • Familiarity with workflow orchestration tools (Databricks Workflows or similar)

Preferred Qualifications (Nice-to-Have)

  • Experience with propensity modeling, customer segmentation, or marketing analytics
  • Exposure to CI/CD concepts for data and ML pipelines
  • Experience  with Docker or containerized deployments
  • Exposure to GenAI, LLMs, or RAG-based systems
  • Master's degree in Computer Science, Statistics, or a related field

Apply