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Machine Learning System Engineer Jobs (NOW HIRING)

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$125 - $150/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... Production ML Systems * Own the complete ML lifecycle from research and prototyping through ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class ... Experience implementing, deploying, and maintaining production machine learning systems.

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class ... Experience implementing, deploying, and maintaining production machine learning systems.

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$150 - $200/hr

Responsible for developing next-generation AI systems designed to simplify task automation for ... machine learning systems to ensure continuous improvement. * Collaborate with software engineers ...

S27a

$150 - $200/hr

Responsible for developing next-generation AI systems designed to simplify task automation for ... machine learning systems to ensure continuous improvement. * Collaborate with software engineers ...

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what ... We're looking for a hands-on Machine Learning Engineer who enjoys turning cutting-edge ML research ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Design, build, and maintain end-to-end ML systems, including synthetic data pipelines, model ...

Speria

Machine Learning Engineer

Atlanta, GA · On-site

$125 - $150/hr

Develop decisioning systems for automated actions * Monitor model performance and improve ... Feature engineering pipelines for Machine Learning * Git, CI/CD, reproducible workflows

ExaCare Inc

Machine Learning Engineer

Manhattan, NY · On-site

$100 - $125/hr

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

International Executive Service Corps

$150 - $200/hr

TheArtificial Intelligence/Machine Learning Systems Engineer willsupport a USG Program Office ... System acquisition, design, development, integration, test, and/or flight operations * Artificial ...

Booz Allen Hamilton

Machine Learning Engineer

Aurora, CO · On-site

$125 - $150/hr

You'll grow within a talented team of machine learning engineers across the company and collaborate with data scientists, physicists, and systems engineers to deliver world-class solutions to develop ...

Modulate

Machine Learning Engineer

Somerville, MA · On-site

$150 - $200/hr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Partner with platform and infrastructure teams to operationalize and monitor ML systems in ...

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Machine Learning System Engineer information

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$127.2K

$167K

How much do machine learning system engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning system engineer in the United States is $127,215.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $157,000.00 per year, depending on experience, location, and employer.

What is a machine learning system engineer?

Machine learning system engineers are professionals who design, build, and maintain the infrastructure and systems that support machine learning models in production environments. They work at the intersection of software engineering and data science, ensuring that machine learning algorithms run efficiently, scale appropriately, and integrate seamlessly with existing applications. Their responsibilities often include data pipeline development, model deployment, monitoring, and optimization to ensure reliable and robust AI solutions.

What are the key skills and qualifications needed to thrive as a machine learning system engineer?

To thrive as a Machine Learning System Engineer, you need strong skills in computer science, statistics, machine learning algorithms, and a degree in a related field such as computer science or engineering. Proficiency with programming languages like Python or Java, experience with ML frameworks (e.g., TensorFlow, PyTorch), and knowledge of cloud platforms are typically required. Exceptional problem-solving abilities, teamwork, and effective communication are vital soft skills that help in designing scalable solutions and collaborating across teams. These skills ensure the successful development, deployment, and maintenance of reliable machine learning systems in real-world environments.

What are some common challenges machine learning system engineers face when deploying models to production environments?

Machine Learning System Engineers often encounter challenges such as ensuring model scalability, maintaining low latency, and addressing data drift once models are deployed in production. They must also work closely with software engineers, data scientists, and DevOps teams to integrate models seamlessly into existing systems and monitor their ongoing performance. Additionally, balancing computational resources and optimizing for cost efficiency while ensuring high reliability can be complex, making collaboration and clear communication essential in this role.

What is the difference between Machine Learning System Engineer vs Data Scientist?

AspectMachine Learning System EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications in ML or cloud platformsBachelor's or Master's in Statistics, Data Science, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops, deploys, and maintains ML systems; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works closely with business teams
Industry UsageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, analytics firms, tech companies

While both roles involve machine learning, Machine Learning System Engineers focus on building and maintaining scalable ML systems, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in technical focus and responsibilities.

What cities are hiring for Machine Learning System Engineer jobs?

Cities with the most Machine Learning System Engineer job openings:

What are popular job titles related to Machine Learning System Engineer jobs?

For Machine Learning System Engineer jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning System Engineer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $127,215 per year, or $61.2 per hour.

Machine Learning Systems Engineer -- Sensor Algorithms

Santa Clara, CA • On-site

Talentlab
See more jobs at Talentlabexternal

$150 - $200/hr

Other

Posted 18 days ago

Job description

Machine Learning Systems Engineer — Sensor AlgorithmsMachine Learning Systems Engineer — Sensor Algorithms

Location: Santa Clara, CA
Focus: Multi-modal sensor fusion, signal processing, ML algorithms

TalentLab is working with a leading semiconductor and edge-computing technology company on an opportunity for a Machine Learning Systems Engineer focused on advanced sensor algorithms.

This is an R&D-oriented role developing algorithms for single and multi-sensor systems used in smartphones, wearables, IoT and other consumer devices. The work sits at the intersection of sensor fusion, signal processing, estimation and machine learning, with responsibility spanning algorithm design, evaluation and eventual deployment onto embedded platforms.

This is not a traditional ML software engineering or model deployment position. We're particularly interested in engineers with strong research foundations in sensor algorithms, signal processing and statistical methods.

What you'll work on

  • Develop algorithms for single and multi-sensor fusion using ML/AI and statistical techniques.
  • Prototype and evaluate algorithms using Python and MATLAB.
  • Work with inertial sensors and IMU data, including accelerometers and gyroscopes.
  • Design strategies for data collection, analysis, validation and benchmarking.
  • Evaluate trade-offs between algorithm performance, computational complexity and power consumption.
  • Translate algorithm designs toward embedded implementation in C/C++.
  • Collaborate with systems, software, integration and test engineers throughout the product lifecycle.

What we're looking for

  • PhD or Master's degree in Electrical Engineering, Computer Engineering or a closely related discipline.
  • Strong background in signal processing, probability, statistics and estimation.
  • Experience with sensor fusion and/or inertial sensing.
  • Understanding of supervised and unsupervised learning, feature extraction, classification and regression.
  • Strong Python and/or MATLAB skills.
  • Hands-on algorithm development, experimentation and debugging experience.
  • Research or publications in sensor fusion, signal processing, estimation or related areas are highly valued.
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