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Freelance Mechanical Engineering Machine Learning Jobs

Data Science & Machine Learning Engineer

$117K - $140K/yr

Required Skills & Responsibilities: * 5+ years of experience in Data Engineering, Machine Learning Engineering, or related fields. * Strong programming expertise in Python (Pandas, NumPy, PySpark ...

Sr. Machine Learning Engineer, Siri Global

Cupertino, CA · On-site

$151K - $199K/yr

We build machine learning models, systems, and software that understands the intents hundreds of ... Software engineering experience with both server-based and client-side (e.g. on-device) models is a ...

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 ...

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 ...

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

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.

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Freelance Mechanical Engineering Machine Learning information

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$17

$33

$54

How much do freelance mechanical engineering machine learning jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for freelance mechanical engineering machine learning in the United States is $33.20, according to ZipRecruiter salary data. Most workers in this role earn between $26.92 and $37.50 per hour, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Highly experienced freelance mechanical engineers working on specialized projects, such as advanced product design or consulting for large corporations, can earn $500,000 or more annually. Achieving this level typically requires extensive expertise, a strong portfolio, and often involvement in high-value contracts or niche markets.

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

Earning $200,000 annually as a mechanical engineer is possible but typically requires extensive experience, advanced skills, and working in high-paying industries such as aerospace or energy. Senior roles, specialized expertise, or managerial positions tend to offer higher salaries, especially in regions with a high cost of living or in companies valuing advanced technical knowledge and certifications. Entry-level or mid-career mechanical engineers usually earn less than this amount.

What is the difference between Freelance Mechanical Engineering Machine Learning vs Freelance Data Scientist?

AspectFreelance Mechanical Engineering Machine LearningFreelance Data Scientist
CredentialsEngineering degrees, certifications in machine learningStatistics, data analysis, programming certifications
Work EnvironmentEngineering firms, manufacturing, product designTech companies, consulting, research labs
Industry UsageProduct development, automation, roboticsData analysis, predictive modeling, business insights

Freelance Mechanical Engineering Machine Learning professionals focus on applying machine learning techniques to mechanical engineering problems, often within manufacturing or product design. In contrast, Freelance Data Scientists analyze data across various industries to generate insights and predictive models. While both roles require machine learning skills, their industry applications and work environments differ significantly.

Can I do freelancing with machine learning?

Freelance mechanical engineering professionals can incorporate machine learning skills to offer specialized services such as predictive maintenance, data analysis, and automation solutions. Success in freelancing with machine learning requires proficiency in programming languages like Python, knowledge of machine learning frameworks, and a strong understanding of engineering principles. Building a portfolio and obtaining relevant certifications can help attract clients in this field.

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 machine learning frameworks, can enhance their ability to transition into this field.
More about Freelance Mechanical Engineering Machine Learning jobs
What cities are hiring for Freelance Mechanical Engineering Machine Learning jobs? Cities with the most Freelance 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 Freelance Mechanical Engineering Machine Learning jobs? States with the most job openings for Freelance Mechanical Engineering Machine Learning jobs include:
What job categories do people searching Freelance Mechanical Engineering Machine Learning jobs look for? The top searched job categories for Freelance Mechanical Engineering Machine Learning jobs are:
Infographic showing various Freelance Mechanical Engineering Machine Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $69,055 per year, or $33.2 per hour.
Mid- level Machine Learning Engineer

Mid- level Machine Learning Engineer

InstantServe LLC

San Jose, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Title: Senior Machine Learning Engineer
Client: TetraMem Inc
Location: San Jose, California
Senior Machine Learning Engineer
About the job
Responsibilities
  • Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
  • Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
  • Work closely with hardware and software teams to integrate ML models into production systems.
  • Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
  • Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
  • Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
  • Provide technical leadership and mentorship to junior engineers.
  • Publish research findings, present at conferences, and contribute to open-source projects when applicable.
Requirements
  • 5+ years of relevant industry experience (or a PhD) in Computer Science, Electrical Engineering, Machine Learning, or related fields.
  • Must have prior experience managing a team, serving in a Team Lead role, or demonstrating strong technical leadership and cross-functional coordination capabilities.
  • Strong hands-on experience in machine learning, with a focus on edge AI, on-device inference, and deploying lightweight models on resource-constrained devices.
  • Expertise in modern ML frameworks such as PyTorch, TensorFlow (including TensorFlow Lite), and JAX.
  • Proficiency in Python and C/C++, with practical experience in ML model optimization and production deployment.
  • Deep experience with model quantization (PTQ/QAT), pruning, knowledge distillation, sparsity, and other compression techniques for efficient edge inference.
  • Hands-on experience developing for or integrating with AI chip SDKs, neural accelerators (NPUs/DSPs), or hardware-specific toolchains (e.g., NVIDIA TensorRT, Qualcomm Neural Processing SDK, ARM Ethos, or similar).
  • Familiarity with edge inference runtimes (ONNX Runtime, ExecuTorch, TVM) and optimizing models for hardware constraints (latency, memory footprint, power consumption).
Experience in one or more of the following areas considered a strong plus:
  • Understanding of ML compiler and runtime design.
  • Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
  • Familiarity with hardware acceleration techniques.
  • Experience in embedded system development.

InstantServe logo

About InstantServe

Sourced by ZipRecruiter

InstantServe provides a one-stop solution to all Healthcare, IT/Non-IT Staffing needs. Established in 2016, InstantServe is a strong workforce of over 100+ go-getters with a demonstrated background in IT/Non-IT service. We are a nationally certified SBE from the Department of Administration (State of PA). As a proud Minority Woman Owned Small Business Enterprise (M/WBE), InstantServe boasts of a strong team of professionals who have extensive experience catering to several Federal, Public, Commercial, and Healthcare Clients which includes 26 States and 46 government agencies. InstantServe is a client-centric organization that offers cost-effective and reliable solutions. Client satisfaction is sacrosanct! Our team strives to provide the best staffing and IT solutions to take your business to the next level.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

Wayne, PA, US

Year founded

2016

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