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Remote Mechanical Engineering Machine Learning Jobs

Serve Robotics

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

You will bridge the gap between core AI research and production-grade engineering, developing ... Employee divides their time between in-office and remote work. Access to an office location is ...

DocuSign

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

You will bridge the gap between core AI research and production-grade engineering, developing ... Employee divides their time between in-office and remote work. Access to an office location is ...

Spotify

Machine Learning Engineer

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Aquent

AI Engineer - Machine Learning 3

Redmond, WA · On-site +1

$80 - $90/hr

Strong technical foundations in software engineering, machine learning, statistics, and experimental design. * Experience building data-intensive applications, machine learning systems ...

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

Above Group

Remote Mechanical Engineer (ME)

Melbourne, FL · On-site +1

Outcome Learning:Results-focused learning that strengthens individual and organizational capacity ... The ME shall execute engineering and design duties as required to ensure quality products. * The ME ...

Above Group

Remote Mechanical Engineer (ME)

Melbourne, FL · On-site +1

Outcome Learning: Results-focused learning that strengthens individual and organizational capacity ... The ME shall execute engineering and design duties as required to ensure quality products. * The ME ...

Genentech

Machine Learning Engineer

South San Francisco, CA · On-site +1

$168K - $312K/yr

The Machine Learning Engineer sits on the Data Science & Machine Learning Team to help the CMG ... Proficient with software engineering best practices, including agile development, code reviews, SCM ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Anno.ai

Senior Machine Learning Engineer

$107K - $146K/yr

Due to the sensitive nature of our engineering work, Anno.ai enforces strict digital footprint and ... Position Overview As a Senior Machine Learning Engineer at Anno.ai, you will design, develop, test ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

... Engineering skills who shares our most important values: * You're fanatical about polish. Every ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. A Ph.D. is a plus. * 5+ years of experience in machine learning and data related roles. * Proven ...

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

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All JobsMechanical Engineering Machine Learning JobsRemote Mechanical Engineering Machine Learning Jobs

Remote Mechanical Engineering Machine Learning information

See salary details

$45.5K

$102.9K

$166.5K

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

As of Jul 14, 2026, the average yearly pay for remote 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 the difference between Remote Mechanical Engineering Machine Learning vs Remote Mechanical Engineering?

AspectRemote Mechanical EngineeringRemote Mechanical Engineering Machine Learning
Required CredentialsBachelor's or Master's in Mechanical EngineeringBachelor's or Master's in Mechanical Engineering; knowledge of Machine Learning
Work EnvironmentDesign, analysis, CAD modeling, testingDesign, analysis, CAD modeling with ML integration, data analysis
Industry UsageManufacturing, automotive, aerospaceManufacturing, automotive, aerospace with AI/ML applications
Common Search/ComparisonYesYes

Remote Mechanical Engineering involves traditional engineering tasks like design and analysis, while Remote Mechanical Engineering Machine Learning combines these with AI techniques to optimize processes and develop intelligent systems. The latter requires additional knowledge of machine learning but shares many core skills and industry applications.

What is a Remote Mechanical Engineering Machine Learning job?

A Remote Mechanical Engineering Machine Learning job combines mechanical engineering expertise with machine learning techniques, allowing professionals to develop intelligent systems and optimize mechanical processes from a remote location. These roles often involve tasks such as analyzing engineering data, building predictive models, automating design tasks, and enhancing product performance using AI algorithms. Working remotely, engineers collaborate with teams through digital platforms, contributing to research, development, and deployment of machine learning solutions in mechanical engineering applications.

What are some typical challenges faced by remote mechanical engineers working with machine learning, and how can they be managed?

Remote mechanical engineers who work with machine learning often face challenges such as effective cross-functional collaboration, accessing and sharing large datasets, and keeping communication clear across distributed teams. To manage these, it's important to leverage collaborative tools for version control, data management, and regular virtual meetings. Building strong communication habits and proactively seeking feedback from data scientists, software engineers, and other stakeholders will help ensure project alignment and smooth workflows.
More about Remote Mechanical Engineering Machine Learning jobs
What cities are hiring for Remote Mechanical Engineering Machine Learning jobs? Cities with the most Remote 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 Remote Mechanical Engineering Machine Learning jobs? States with the most job openings for Remote Mechanical Engineering Machine Learning jobs include:
What job categories do people searching Remote Mechanical Engineering Machine Learning jobs look for? The top searched job categories for Remote Mechanical Engineering Machine Learning jobs are:
Remote Mechanical Engineering Machine Learning jobs near you
Infographic showing various Remote Mechanical Engineering Machine Learning job openings in the United States as of July 2026, with employment types broken down into 25% Internship, 50% Full Time, and 25% Contract. Highlights an 100% Remote job distribution, with an average salary of $102,878 per year, or $49.5 per hour.
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Serve Robotics

On-site, Remote

$225K - $260K/yr

Full-time

Posted 18 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.
Responsibilities
  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
  • Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
  • Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
  • Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
  • Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
  • Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
  • Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
  • Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications
  • Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
  • Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
  • Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
  • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
  • Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out
  • Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
  • Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
  • Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
  • Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $177k - $215k CAD

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