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Remote Embedded Machine Learning Jobs in Santa Clara, CA

Match Group

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$114K - $156K/yr

Machine Learning Software Engineers who bridge the gap between research and production by ... are embedded in core Tinder user flows at scale. Where You'll Work: This is a hybrid role and ...

Match Group

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$145K - $165K/yr

Machine Learning Software Engineers who bridge the gap between research and production by ... are embedded in core Tinder user flows at scale. Where You'll Work: This is a hybrid role and ...

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

The ideal candidate will have a strong background in machine learning and data science and a proven ... Optimize algorithms for running on embedded devices and in the cloud * Design and run experiments ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Santa Clara, CA

Remote Embedded Machine Learning information

See Santa Clara, CA salary details

$82.2K

$180.1K

$204.4K

How much do remote embedded machine learning jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote embedded machine learning in Santa Clara, CA is $180,139.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,400.00 and $203,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in Santa Clara, CA? The most popular types of Embedded Machine Learning jobs in Santa Clara, CA are:
What are popular job titles related to Remote Embedded Machine Learning jobs in Santa Clara, CA? For Remote Embedded Machine Learning jobs in Santa Clara, CA, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Santa Clara, CA look for? The top searched job categories for Remote Embedded Machine Learning jobs in Santa Clara, CA are:
What cities near Santa Clara, CA are hiring for Remote Embedded Machine Learning jobs? Cities near Santa Clara, CA with the most Remote Embedded Machine Learning job openings:
Remote Embedded Machine Learning jobs near you
Machine Learning Engineer II

Machine Learning Engineer II

Match Group

Palo Alto, CA • On-site, Remote

$114K - $156K/yr

Other

Re-posted 8 days ago

Job description

Our Mission

As humans, there are few things more exciting than meeting someone new. At Tinder, we're inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive-and rapidly growing. 

We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.


Our Values
  • Take the Lead: We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down.
  • Move Fast: We have a bias for action and urgency. Something that could be done tomorrow would be better if done today.
  • Better Together: We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate.
  • Real Talk: We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same.
  • Safety First: We act with integrity, transparency, and consistency so people feel safe-whether they're swiping, matching, or working alongside us.
  • Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.

The Team:

The Tinder ML team drives impact across nearly every core domain of the product - Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder's ecosystem.

ML at Tinder is organized into three groups with distinct roles:

  • Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation

  • Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management

  • Machine Learning Software Engineers who bridge the gap between research and production by delivering machine learning models into real-world product experiences at scale

About the Role:

We are looking for a Machine Learning Engineer II to help build and ship machine learning systems that improve product experience and drive measurable business impact. This role is ideal for an engineer with a strong foundation in machine learning and software engineering who is excited to work on real-world problems, partner cross-functionally, and grow quickly in a high-impact environment.

This is an individual contributor role focused on modeling and algorithmic innovation. You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from development into production. The team's work directly translates into measurable business outcomes, and many of its models are embedded in core Tinder user flows at scale.

Where You'll Work: 

This is a hybrid role and requires in-office collaboration three times per week in Palo Alto, California.

In this role, you will:
  • Translate product and business problems into clear machine learning problems with measurable success criteria
  • Build, train, evaluate, and improve production machine learning models
  • Partner with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production
  • Design and analyze offline evaluations and online experiments to understand model impact
  • Contribute to feature engineering, data preparation, training pipelines, and model monitoring
  • Write clean, maintainable, production-quality code and participate in design and code reviews
  • Communicate technical findings, trade-offs, and recommendations clearly to both technical and non-technical partners
You'll need:
  • BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field
  • 1+ year of industry experience in machine learning, software engineering, data science, or a related field
  • Strong foundation in computer science fundamentals, including data structures, algorithms, and software design
  • Experience building ML or AI-related systems, or strong understanding of how modern machine learning systems are developed and operated
  • Proficiency in Python and at least one additional programming language such as Java, Kotlin, Go, Scala, or a similar language
  • Strong understanding of machine learning fundamentals, including model training, evaluation, and experimentation
  • Strong communication skills and the ability to collaborate effectively across functions
  • Self-motivated, proactive, and comfortable taking ownership of well-scoped problems
Nice to have:
  • Experience with recommendation systems or casual inference
  • Familiarity with big data or stream processing frameworks such as Spark or Flink
  • Familiarity with cloud platforms such as AWS and containerized environments such as Kubernetes
  • Familiarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve
  • Experience with feature stores, ML data pipelines, and orchestration frameworks such as Airflow
  • Understanding of MLOps practices including CI/CD for ML, model versioning, and automated evaluation
  • Exposure to observability and monitoring for ML systems
  • Exposure to LLM-related use cases or applied generative AI projects
$145,000 - $165,000 a year

The salary range for this position is $145,000 - $165,000.  Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in Palo Alto, California. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

Commitment to Inclusion
 
At Tinder, we don't just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don't meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei
 
If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.
 
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