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Machine Learning System Engineer Jobs (NOW HIRING)

FloVision Solutions

Machine Learning Engineer

Working knowledge of MLOps practices and the principles required to deploy, monitor, and maintain reliable machine learning systems in production * Strong analytical, programming, and problem-solving ...

FloVision Solutions

Machine Learning Engineer

OR · On-site +1

Working knowledge of MLOps practices and the principles required to deploy, monitor, and maintain reliable machine learning systems in production * Strong analytical, programming, and problem-solving ...

Thorn

Staff Machine Learning Engineer

Lead machine learning system designs, set engineering standards, lead technical meetings and proactively engage and mentor other engineers * Help debug, do code review, and support general machine ...

ManTech International

Machine Learning Engineer

$128K - $214K/yr

... system performance. * Train and embed machine learning models into applications using programming ... languages (Python, Java, R) and core libraries (TensorFlow, Keras, Scikit-learn). * Explore and ...

Apple

Machine Learning Engineer

Santa Clara, CA · On-site

Our team comprises a diverse range of backgrounds, including applied machine learning engineers with a focus on ML and LLM, and experienced distributed systems engineers. As such, we are seeking ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Design machine learning systems * Research and implement appropriate ML algorithms and tools ... Engineer or a similar role * Strong experience with Deep Learning * Understanding of data ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Design machine learning systems * Research and implement appropriate ML algorithms and tools ... Engineer or a similar role * Strong experience with Deep Learning * Understanding of data ...

Lyft

Machine Learning Engineer

New York, NY · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define ... Evaluate ML system performance against business KPIs, run experiments, and drive continuous model ...

Lyft

Machine Learning Engineer

New York, NY · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define ... Evaluate ML system performance against business KPIs, run experiments, and drive continuous model ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Description We design, build, and maintain large-scale ML systems that make petabytes of data easy ... machine learning models, with a strong understanding of data and model quality Strong programming ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

They are seeking an Applied Machine Learning Engineer to develop products for their clients and the ... systems. Responsibilities : • Study and transform data science prototypes • Design machine ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

Goodfire is a research company focused on understanding and designing AI systems. They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying ...

Socket.dev

Machine Learning Engineer

Los Angeles, CA · On-site

Backed by USC and Techstars, we're creating the software, data, and intelligence systems that help ... Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ...

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define ... Evaluate ML system performance against business KPIs, run experiments, and drive continuous model ...

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Our highly motivated Machine Learning Engineers work on these challenging problems and define ... Evaluate ML system performance against business KPIs, run experiments, and drive continuous model ...

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Machine Learning System Engineer information

See salary details

$53.5K

$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 Engineer

San Francisco, CA • On-site

RZR Global Inc.
See more jobs at RZR Global Inc.external

Full-time

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

Job description

Who are we?

RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.

Role Overview

We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.

Key Responsibilities

  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.

  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.

  • Analyze the impact of integrating new data sources and features into our models.

  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.

  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.

  • Document experiments, assumptions, and outcomes; maintain reproducibility

Required Skills / Experience

  • Bachelor's or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.

  • At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.

  • Experience with machine learning techniques such as regression, classification, and clustering.

  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).

  • Strong grasp of probability, statistics, and data analysis principles.

  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.

Nice-to-Have

  • Familiarity with system programming languages including C++ and Rust is a plus.

  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)

  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.

Apply