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Senior Staff Machine Learning Engineer Jobs in California

GEICO

Senior Staff Machine Learning Engineer

Palo Alto, CA · On-site

$122K - $168K/yr

GEICO is seeking a Senior Staff AI engineer to join our AI org. This person will play key senior technical leadership roles in the development of Geico's virtual agent platform that elevates the ...

Geico

Senior Staff Machine Learning Engineer

Palo Alto, CA · On-site

$122K - $168K/yr

GEICO is seeking a Senior Staff AI engineer to join our AI org. This person will play key senior technical leadership roles in the development of Geico's virtual agent platform that elevates the ...

Omnissa

Staff Machine Learning Engineer

Mountain View, CA · On-site

$162K - $342K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.

Hive

Staff Machine Learning Engineer

San Francisco, CA · On-site

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Hive

Staff Machine Learning Engineer

San Francisco, CA

$200K - $300K/yr

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA · On-site

$202K - $274K/yr

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll be embedded inside a vibrant team of data scientists. You'll be expected to help conceive, code, and deploy data science ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA

$202K - $274K/yr

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll be embedded inside a vibrant team of data scientists. You'll be expected to help conceive, code, and deploy data science ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA · On-site

$10/hr

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll be embedded inside a vibrant team of data scientists. You'll be expected to help conceive, code, and deploy data ...

Shipt

Staff Machine Learning Engineer

San Francisco, CA · On-site

Impact As a Staff Machine Learning Engineer on Shipt's Personalization Platform team you will drive ... You will be a hands-on senior technical contributor in the Membership organization and your work ...

Suki

Staff Machine Learning Engineer

Redwood City, CA · On-site

The Staff Machine Learning Engineer will drive innovation on the Machine Learning team, focusing on NLP and improving technical approaches to support healthcare professionals. Responsibilities : • ...

Adobe

Staff Machine Learning Engineer

San Jose, CA · On-site +1

As a Staff Machine Learning Engineer (MLE 50), you will design, build, and deploy semantic matching and ranking models that understand text, images, documents, and other content modalities at Adobe ...

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Showing results 21-40

All JobsStaff Machine Learning Engineer JobsSenior Staff Machine Learning Engineer JobsSenior Staff Machine Learning Engineer Jobs in California

Senior Staff Machine Learning Engineer information

See California salary details

$58.7K

$124.9K

$181.1K

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

As of Aug 11, 2026, the average yearly pay for senior staff machine learning engineer in California is $124,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,100.00 and $141,600.00 per year, depending on experience, location, and employer.

What are the primary challenges a senior staff machine learning engineer faces when leading large-scale ML projects?

Senior Staff Machine Learning Engineers often navigate complex challenges such as aligning cross-functional teams, ensuring model scalability, and maintaining data integrity across evolving pipelines. They are responsible for setting technical direction, mentoring junior engineers, and driving collaboration between data scientists, software engineers, and product managers. Balancing hands-on technical work with high-level architectural decisions, while also keeping up with rapid advancements in the field, is key to success in this role.

What does a senior staff machine learning engineer do?

A Senior Staff Machine Learning Engineer leads the design, development, and deployment of complex machine learning systems within an organization. They work closely with cross-functional teams to identify business challenges that can be addressed with machine learning and guide the technical strategy for implementing solutions. Their responsibilities often include mentoring junior engineers, setting best practices, overseeing large-scale projects, and ensuring models are robust, scalable, and ethically implemented. Additionally, they may contribute to research and development, staying up-to-date with the latest advancements in the field.

What is the difference between Senior Staff Machine Learning Engineer vs Machine Learning Engineer?

AspectSenior Staff Machine Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's/PhD in CS, AI, or related; experience in ML frameworksBachelor's/Master's in CS, AI, or related; some experience in ML
Work EnvironmentLeadership roles, cross-team collaboration, strategic planningImplementation, model development, experimentation
Industry UsageTech companies, research labs, large enterprisesStartups, tech firms, research projects

The Senior Staff Machine Learning Engineer typically holds a more senior, strategic role with leadership responsibilities, while the Machine Learning Engineer focuses on developing and deploying ML models. Both roles require strong technical skills, but the senior position involves guiding projects and mentoring teams.

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

To thrive as a Senior Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, software engineering, and a relevant advanced degree (often MS or PhD). Mastery of tools such as Python, TensorFlow, PyTorch, distributed computing frameworks, and experience with cloud platforms is typically required. Strong leadership, communication, and project management skills distinguish top performers in this role. These abilities are crucial for designing scalable ML solutions, leading teams, and driving impactful business outcomes.
What are popular job titles related to Senior Staff Machine Learning Engineer jobs in California? For Senior Staff Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Senior Staff Machine Learning Engineer jobs in California look for? The top searched job categories for Senior Staff Machine Learning Engineer jobs in California are:
What cities in California are hiring for Senior Staff Machine Learning Engineer jobs? Cities in California with the most Senior Staff Machine Learning Engineer job openings:
Senior Staff Machine Learning Engineer jobs near you
Infographic showing various Senior Staff Machine Learning Engineer job openings in California as of August 2026, with employment types broken down into 2% As Needed, 77% Full Time, 16% Part Time, 2% Temporary, and 3% Contract. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution, with an average salary of $124,900 per year, or $60 per hour.

Staff Machine Learning Engineer

AppFolio, Inc

Santa Barbara, CA • On-site

$200 - $250/hr

Other

Re-posted 10 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

181st of 242 rated software companies

Job description

Staff Machine Learning Engineer – Software Engineering

Locations: Santa Barbara, CA; San Diego, CA; Remote - San Francisco, CA; Remote - Denver, CO.

Overview

We’re building an AI‑native platform for the real estate industry and are looking for a Staff Machine Learning Engineer to advance the ML platform that underpins all of AppFolio’s AI initiatives.

Your Impact
  • ML Platform: Design and operate AppFolio’s ML infrastructure on AWS – ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls.
  • Drive AI Cost Discipline: Optimize cost across all AI applications – provider routing, caching, batch vs. real‑time, model-size selection, and inference economics.
  • Multi‑Provider Reliability: Maintain reliable, multi‑provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions.
  • Training & Fine‑Tuning Stack: Build the training and fine‑tuning stack for small language models, including data pipelines, GPU orchestration, and evaluation.
  • Productionize Research: Partner with Voice & Agents and Research ML engineers to harden prototypes into production systems with SLOs, on‑call rotations, and observability.
  • AI Safety & Guardrails: Operate AppFolio’s AI safety and authorization layer – guardrails on AWS, scoped tool permissions, and human‑in‑the‑loop gates for autonomous agent actions.
Qualifications
  • Systems thinker: Think in terms of platforms and long‑term leverage, not just features.
  • Production builder: Built and scaled ML infrastructure in production with meaningful business impact.
  • Ambiguity: Operate effectively in high ambiguity, turning unclear infra problems into clear direction.
  • Owner‑operator: Take ownership with a founder/owner‑operator mindset, act with urgency, and focus on outcomes.
  • Pace: Strong desire to move fast and deliver impact while maintaining sound engineering judgment.
  • Collaboration: Humble, collaborative, low‑ego, and elevate those around you.
  • Sustainability: Value work‑life balance as a foundation for sustained high performance.
  • Reliability mindset: Treat ML infra like any other production system – SLOs, on‑call, observability, postmortems.
Must Have
  • ML infra at scale: Built and operated production ML infrastructure on AWS – ECS, SageMaker, GPUs, autoscaling, and cost controls.
  • Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing.
  • Provider breadth: Direct experience integrating with Google (Vertex/Gemini), OpenAI, and Anthropic APIs in production.
  • Training capability: Trained or fine‑tuned language models end‑to‑end; comfortable with deep learning, evaluation, and inference.
  • Cloud‑native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads.
  • RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data.
  • Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency.
  • AI safety & authorization: Hands‑on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems.
Nice to Have
  • Experience training small language models for production use.
  • GPU performance tuning (vLLM, TensorRT, Triton, or similar).
  • Prior staff‑level role at a company with a significant AI infra footprint.
  • Experience with ontology‑driven systems or knowledge graphs supporting AI applications.
  • Contributions to open‑source ML infrastructure or LLM tooling.
Compensation & Benefits
  • Base pay range: $200,000 – $250,000. Additional benefits and bonuses may apply.
  • Regular full‑time employees are eligible for benefits.
Statement of Equal Opportunity

At AppFolio, we value diversity in backgrounds and perspectives. We are a proud Equal Opportunity Employer and welcome applicants of all races, colors, religions, sexes, sexual orientations, gender identifications, national origins, ages, marital statuses, ancestries, physical or mental disabilities, or veteran status.

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