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Remote Machine Learning Software Engineer Jobs in Santa Clara, CA

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

New

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 ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$196K - $221K/yr

As a Machine Learning Engineer, you'll bring your strong software engineering mindset to machine learning in order to scale and optimize our ML systems-creating and transforming innovative research ...

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Collaborate as part of a cross-functional Agile team to create and enhance software that enables ...

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Showing results 1-20

Remote Machine Learning Software Engineer information

See Santa Clara, CA salary details

$74.6K

$173.3K

$241.3K

How much do remote machine learning software engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for remote machine learning software engineer in Santa Clara, CA is $173,257.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,900.00 and $203,200.00 per year, depending on experience, location, and employer.

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

AspectRemote Machine Learning Software EngineerRemote Data Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, coding, deploying algorithmsAnalyzing data, building models, interpreting results
Industry UsageTech, finance, healthcare, e-commerceTech, finance, healthcare, research institutions

While both roles involve working with data and algorithms, Remote Machine Learning Software Engineers focus on developing and deploying machine learning models through coding, whereas Remote Data Scientists analyze data to extract insights and build statistical models. Both roles often collaborate but serve different primary functions within organizations.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Santa Clara, CA?

The most popular types of Machine Learning Software Engineer jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Remote Machine Learning Software Engineer jobs?

Cities near Santa Clara, CA with the most Remote Machine Learning Software Engineer job openings:

Infographic showing various Remote Machine Learning Software Engineer job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $173,257 per year, or $83.3 per hour.

Software Engineer, Core Machine Learning

Sunnyvale, CA • On-site, Remote


Meta
Internet and IT • 10K+ employees

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 246 rated software companies

People enjoy working here

Good employer

Recommended by students


$183K/yr

Full-time

Re-posted 6 days ago


Job description

Meta is seeking a Staff Software Engineer to join the Core Machine Learning team, focused on building and scaling the foundational ML infrastructure and systems that power Meta's family of products. In this role, you will architect and deliver high-impact ML platform capabilities — spanning training infrastructure, model serving, feature engineering pipelines, and AI-accelerated developer tooling — that enable thousands of engineers and researchers across Meta to build and ship state-of-the-art machine learning models at scale.
Software Engineer, Core Machine Learning Responsibilities:
  • Architect and own large-scale ML infrastructure systems, including distributed training frameworks, model serving platforms, and feature computation pipelines that support production workloads across Meta's product surface
  • Lead the technical design and implementation of foundational ML platform components, evaluating trade-offs across performance, reliability, and developer experience
  • Drive end-to-end delivery of major ML infrastructure initiatives, coordinating across teams and disciplines to align on priorities, manage dependencies, and execute phased rollouts
  • Identify and resolve performance bottlenecks in ML training and inference systems through instrumentation, profiling, and targeted optimization
  • Define and enforce service level objectives for core ML platform services, building dashboards, alerting systems, and runbooks to reduce mean time to mitigation during incidents
  • Establish and advocate for engineering best practices in ML systems development, including testing strategies, safe rollout patterns, and AI-accelerated development workflows
  • Collaborate with research, product engineering, and infrastructure teams as a credible technical co-owner, independently driving design reviews, data analyses, and architectural decisions
  • Mentor other engineers on ML systems design, debugging complex distributed system issues, and applying AI tools to accelerate development velocity
  • Contribute to the team's technical roadmap by identifying opportunities to improve ML platform capabilities and obtaining buy-in from key stakeholders across the organization

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience in software engineering with a focus on machine learning systems, ML infrastructure, or large-scale distributed systems
  • Experience designing and implementing production ML systems such as distributed training frameworks, model serving infrastructure, or large-scale feature engineering pipelines
  • Experience leading major technical initiatives from design through production, including cross-team coordination and phased rollout management
  • Experience with performance analysis and optimization of ML training or inference workloads, including profiling, instrumentation, and bottleneck resolution
  • Experience communicating technical decisions and trade-offs in writing to both engineering and non-engineering stakeholders through design documents, architectural proposals, or postmortems

Preferred Qualifications:
  • Experience defining and operating ML platform reliability programs, including resiliency testing, SLO frameworks, and incident retrospective processes
  • Experience building or contributing to open-source ML frameworks or platform tooling such as PyTorch, TensorFlow, Ray, or similar systems
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience applying AI-assisted development tools to accelerate engineering workflows, including code generation, automated testing, or intelligent debugging
  • Experience with hardware-software co-design for ML workloads, including quantization, model compression, or resource-efficient AI techniques
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.


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