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Remote Senior Machine Learning Engineer Jobs in Concord, CA

EvenUp

Staff Machine Learning Engineer

San Francisco, CA · Remote

$212K - $301K/yr

... senior engineers, and driving decisions that shape both product outcomes and company growth. What ... Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs. Benefits ...

Elicit

Machine Learning Engineer

Oakland, CA · On-site +1

... role As a Machine Learning Engineer at Elicit, you'll build products and workflows that help ... Senior (L4): $220-260K + equity * Expert/Staff (L5): $250-320K + significant equity We're ...

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Remote Senior Machine Learning Engineer information

See Concord, CA salary details

$82.8K

$157.2K

$210.7K

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

As of Aug 15, 2026, the average yearly pay for remote senior machine learning engineer in Concord, CA is $157,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,400.00 and $177,200.00 per year, depending on experience, location, and employer.

How do remote senior machine learning engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

What are the key skills and qualifications needed to thrive as a remote senior machine learning engineer, and why are they important?

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What does a remote senior machine learning engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Concord, CA?

For Remote Senior Machine Learning Engineer jobs in Concord, CA, the most frequently searched job titles are:

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Remote Senior Machine Learning Engineer jobs near you

Sr. Software Engineer, Machine Learning, tvScientific

Pinterest

San Francisco, CA • On-site, Remote

$144K - $190K/yr

Full-time

Re-posted 20 days ago

Job description

About tvScientific

tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.

As a Sr. Machine Learning Engineer at tvScientific, you'll build the ML and AI systems behind our Connected TV ad-buying platform: real-time bidding, campaign optimization, and incrementality measurement at scale. We're an adtech company solving a hard problem: making CTV advertising actually measurable. Our platform helps advertisers buy ads across the CTV ecosystem: Hulu, Pluto TV, Disney+, HBO Max, and hundreds of FAST channels: and prove that those ads drove real business outcomes.


What you'll do:

  • Write production Python that powers real-time bidding, model training, and campaign optimization
  • Train, deploy, and monitor ML models that decide which ads to show, when, and at what price: millions of bid decisions per second
  • Build and improve our incrementality measurement systems: helping advertisers understand the true causal lift of their CTV spend
  • Design and implement new ML products across the ad-buying lifecycle: audience targeting, bid optimization, pacing, and attribution
  • Use LLMs and generative AI to build internal tools that accelerate how we develop, test, and ship ML systems
  • Serve as a technical lead and mentor on a distributed engineering team


What we're looking for:

  • Strong production Python skills: you write code that runs in prod, not just notebooks
  • Solid statistics and ML fundamentals: you can reason about experiment design, model evaluation, and when simpler approaches beat complex ones
  • Familiarity with modern AI tools and good judgment about where they add value
  • Adtech or CTV experience: familiarity with RTB, programmatic advertising, supply-path optimization
  • Clear written communication: we're a distributed team and writing is how decisions get made
  • Comfort with ambiguity: you'll own problems end-to-end in a fast-moving environment, from scoping to shipping
  • Bachelor's degree in Computer Science, Mathematics, Engineering, related field, or equivalent experience
  • 4+ years of industry experience
  • Nice-to-Haves:
    • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
    • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
    • Causal inference: uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
    • Big data experience with Scala and Spark
    • Systems programming experience in Zig or similar (C, C++, Rust)
    • Reinforcement learning or bandit algorithms in production
    • Experience building agentic AI systems or LLM-powered workflows
    • MLOps experience: model deployment, monitoring, and pipeline orchestration on AWS

In-Office Requirement Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.


Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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