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Senior Machine Learning Engineer Jobs in Fairfield, CA

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two ... We are primarily hiring for senior and staff-level engineers who are comfortable owning critical ...

Salesforce, Inc.

Senior ML Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Senior Member of Technical Staff - Senior Machine Learning Engineering Job Category: Software Engineering Job Details About Salesforce We're Salesforce, the Customer Company, inspiring the future of ...

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Senior Machine Learning Engineer information

See Fairfield, CA salary details

$60.6K

$128.8K

$186.7K

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

As of Sep 3, 2026, the average yearly pay for senior machine learning engineer in Fairfield, CA is $128,796.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $146,000.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

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

The most popular types of Machine Learning Engineer jobs in Fairfield, CA are:

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

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

What job categories do people searching Senior Machine Learning Engineer jobs in Fairfield, CA look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Fairfield, CA are:

What cities near Fairfield, CA are hiring for Senior Machine Learning Engineer jobs?

Cities near Fairfield, CA with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Fairfield, CA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $128,796 per year, or $61.9 per hour.

Senior Machine Learning Engineer

Retell AI

San Francisco, CA • On-site

$225K - $325K/yr

Full-time

Medical, Dental, Vision

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

Job description

ABOUT RETELL AI
Retell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.
Our vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI "workers" that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.
We're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.
Let's build the future together.
Recent recognition:
  • No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026
  • Top 50 AI Apps, a16z (2025)
  • #3 Fastest-Growing Software Company, G2 Best Software Awards 2026
  • Best Agentic AI Software, G2 Best Software Awards 2026
  • #4 Fastest-Growing Software Vendor, Brex Benchmark 2025
  • Enterprise Tech 30 Class of 2026, Nasdaq & Wing VC
  • Top-Ranked Startup, Lean AI Leaderboard
  • Backed by Y Combinator

ABOUT THE ROLE
Retell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!
This is a hands-on, high-ownership role for ML engineers who want to build production models that actually ship, and perform under real-world constraints. As a Founding Senior Machine Learning Engineer at Retell, you'll work across the ML stack to power human-like voice agents that handle millions of real-time phone conversations.
You'll fine-tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency-sensitive, high-traffic systems. You'll own model performance end-to-end-from training pipelines to post-deployment monitoring-and shape our ML strategy alongside the founding team.
If you're excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.
KEY RESPONSIBILITIES
  • Train & Tune Models - Fine-tune LLMs and audio models to maximize speed, accuracy, and production-readiness-pushing the frontier of real-time AI voice experiences.
  • Benchmark & Evaluate - Build datasets, define rigorous metrics, and measure model performance across high-impact voice AI tasks to guide development.
  • Deploy to Production - Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale.
  • Run Human Evaluations - Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.
  • Level Up Infrastructure - Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment.

YOU MIGHT THRIVE IF YOU
  • ML Engineer with Real-World Experience - You've trained and shipped models in production. Bonus if you've worked with LLMs or audio models.
  • Fluent in Modern ML Stack - You know your way around Python, PyTorch, and today's ML tools-from training pipelines to evaluation benchmarks.
  • Execution-Oriented - You move fast, take ownership, and focus on solving real problems over perfect ones.
  • Startup-Ready - You're adaptable, resilient, and energized by ambiguity and fast-changing priorities.
  • Clear Communicator & Team Player - You collaborate well across functions and push decisions forward.

JOB DETAILS
  • Cash: $225,000 - $325,000 base salary
  • Equity: Offers Equity
  • Location: Redwood City, CA, US
  • US Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas.

OTHER BENEFITS
  • 100% coverage for medical, dental, and vision insurance
  • $70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks
  • $200/month wellness reimbursement (gym, fitness classes, etc.)
  • $300/month commuter reimbursement (gas, Caltrain, etc.)
  • $75/month phone bill reimbursement
  • $50/month internet reimbursement

COMPENSATION PHILOSOPHY
  • Best Offer Upfront: Choose from three cash-equity balance options, no negotiation needed.
  • Top 1% Talent: Above-market pay (top 5 percentile) to attract high performers.
  • High Ownership: Small teams, >$1M revenue/employee, and significant equity.
  • Performance-Based: Offers tied to interview performance, not experience or past salaries.

INTERVIEW PROCESS
  • Talent Screen (15min): chat with our recruiter to get a better sense of the role, the team, and what it's like to work here.
  • Technical Interview (45 min): MLE coding
  • Technical Interview (45 min): ML questions deepdive
  • Onsite/Virtual Interviews (3 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:
    1. ML System Design: A non-coding interview focused on whiteboarding and high-level system architecture.
    2. ML Question Deep Dive: In-depth discussion exploring your approach to a machine learning problem.
    3. Backend + AI Practical: A hands-on coding interview combining backend development with AI integration.

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