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Machine learning engineer Jobs in Oakland, CA

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Machine learning engineer • oakland ca

Last updated: 7 hours ago

Staff Machine Learning Engineer

app folioRemote - San Francisco, CA
$200,000.00–$275,000.00 yearly$200,000.00–$275,000.00 yearly
RemoteRemote
Full-timeFull-time

Hi, We're AppFolioWe're innovators, changemakers, and collaborators.We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do busine... Show more

Engineering Manager, Machine Learning

sentrySan Francisco, CA, United States
$220,000.00–$280,000.00 yearly$220,000.00–$280,000.00 yearly
Full-timeFull-time

Software runs the world and the pace is faster than ever.Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time build... Show more

Machine Learning Platform Engineer, Machine Learning (ML) and Artificial Intelligence (AI)

parallel partnersSan Francisco, California, United States
RemoteRemote
Full-timeFull-time

Machine Learning Platform Engineer, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home.As the Machine Learning Platform Engineer, you will build the infrastructure and ... Show more

Senior Engineering Manager, Machine Learning

checkrSan Francisco, CA, United States
Full-timeFull-time

Senior Engineering Manager, Machine Learning.San Francisco, California, United States.Checkr is building the data platform to power safe and fair decisions.Over 140,000 companies and millions of pe... Show more

Manager, Machine Learning Engineering

go fund meSan Francisco, CA, United States
Full-timeFull-time

Manager, Machine Learning Engineering.Join GoFundMe as our next Manager, Machine Learning Engineering (ML and AI Operations).In this role, you will lead the team responsible for the infrastructure,... Show more

Machine Learning Software Engineer Intern - Summer 2027

ripplingSan Francisco, California, United States, 94104
Full-timeFull-time
Quick Apply

Rippling gives businesses one place to run HR, IT, and Finance.It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and co... Show more

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home

next step systems recruiters for information technology jobs top it recruiting firmSan Francisco, CA, USA
RemoteRemote
Full-timeFull-time

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home.As Machine Learning Lead Engineer, you own the execution layer of our intelligence, turning research and model capabil... Show more

Machine Learning Engineer / UNICORN / Hybrid in SF

motion recruitmentSan Francisco, California, United States
Full-timeFull-time

A health technology company at the top of their industry is seeking a Machine Learning Engineer to join its research and development team.This full-time opportunity offers the chance to build advan... Show more

Machine Learning Engineer, Implicit Signals

open aiSan Francisco
Full-timeFull-time

Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior.We combine machine learning and production engineering to ... Show more

 • New!

Machine Learning Expert

mercorSan Francisco, California, United States
$70.00–$120.00 hourly$70.00–$120.00 hourly
RemoteRemote
Part-timePart-time
Quick Apply

Headquartered in San Francisco, our investors include.Write modeling problems from systems you have shipped, including data, objectives, constraints, and reference answers for model grading.Grade m... Show more

Machine Learning Research Manager

rad aiSan Francisco, CA, United States
Full-timeFull-time

Machine Learning Research Manager.We're looking for a Machine Learning Research Manager to lead a dedicated, high-impact team of applied and clinical researchers working at the intersection of clin... Show more

Machine Learning Engineer

swish analyticsSan Francisco, California, United States
Full-timeFull-time

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products.We believe that oddsmaking is a challenge rooted in engi... Show more

Machine Learning Engineer - Infrastructure

transparent search groupSan Francisco, California, United States
Full-timeFull-time
Quick Apply

Machine Learning Engineer - Infrastructure.Confidential — venture-backed technology company.San Francisco, CA (South Park office, in person 5 days per week; relocation provided).Visa transfers; can... Show more

Sr. Machine Learning Engineer

general motorsSan Francisco, California, United States of America
$174,900.00–$250,200.00 yearly$174,900.00–$250,200.00 yearly
Full-timeFull-time

GM is developing the next generation of embedded platform software to deliver state-of-the-art ADAS features to our customers.We are looking for an expert Sr.Camera ISP Engineer to join our Autonom... Show more

Senior Machine Learning Engineer - ESPN

disney entertainment espn product technologySan Francisco, Californie, États-Unis
Full-timeFull-time

Disney Entertainment & ESPN Technology.On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories ... Show more

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home

next step systemsSan Francisco, California, United States
RemoteRemote
Full-timeFull-time

Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home.As Machine Learning Lead Engineer, you own the execution layer of our intelligence, turning research and model capabil... Show more

Machine Learning Manager

hiveSan Francisco, CA, United States
$180,000.00–$250,000.00 yearly$180,000.00–$250,000.00 yearly
Full-timeFull-time

In order to execute our vision, we're constantly growing our machine learning team.We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their... Show more

Staff Machine Learning Engineer

databricksSan Francisco, California
$190,000.00–$285,000.00 yearly$190,000.00–$285,000.00 yearly
Full-timeFull-time

The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products.Over the past years, we’ve launched , , and working with product teams, and made significant strides in L... Show more

Machine Learning Operations Analyst

initio capitalSan Francisco, CA, USA
RemoteRemote
Full-timeFull-time
Quick Apply

Initio Capital is hiring for this role and related opportunities across consulting, finance, product, software, AI, operations, market research, and growth-focused workstreams.As a Machine Learning... Show more

 • New!

Machine Learning Director

pay joySan Francisco, CA, United States
Full-timeFull-time

PayJoy, a Public Benefit Corporation, is a mission-first credit provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success.Our patented tech... Show more

People also ask
Staff Machine Learning Engineer

Staff Machine Learning Engineer

app folioRemote - San Francisco, CA
30+ days ago
Salary
$200,000.00–$275,000.00 yearly
Job type
  • Full-time
  • Remote
Job description

Description

Hi, We're AppFolioWe're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.Who We Are Looking ForWe're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on — training, fine-tuning, inference, RAG, evaluation, and cost. You'll keep our AI cloud always-on, observable, and economical, while staying close enough to applications to influence model and agent design.This role works at the intersection of ML infrastructure, applied AI, and cost discipline. You'll partner closely with our Voice & Agents and Research ML engineers to harden their prototypes into production systems, and help move forward the platform layer that lets Realm-X scale across AppFolio's entire customer base.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 their 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

  • You have 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment.
  • Systems thinker: You think in terms of platforms and long-term leverage, not just features.
  • Production builder: You've built and scaled ML infrastructure in production with meaningful business impact.
  • Ambiguity: You operate effectively in high ambiguity, turning unclear infra problems into clear direction.
  • Owner-operator: You take ownership with a founder/owner-operator mindset, act with urgency, and focus on outcomes.
  • Pace: You have a strong desire to move fast and deliver impact, while maintaining sound engineering judgment.
  • Collaboration: You are humble, collaborative, and low-ego, and you elevate those around you.
  • Sustainability: You value work-life balance as a foundation for sustained high performance.
  • Reliability mindset: You treat ML infra like any other production system — SLOs, on-call, observability, postmortems.

Must Have

  • ML infra at scale: Has 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: Has 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

  • Bachelor’s, Master’s, or Ph.D. in Computer Science or related technical discipline.
  • 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.

LocationFind out more about our locations by visiting our . All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.Compensation & BenefitsThe compensation that we reasonably expect to pay for this role is: $200,000 - $275,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.Regular full-time employees are eligible for benefits - .style="color:#ffffff;">#LI-KB1

About AppFolio

AppFolio is the technology leader powering the future of the real estate industry. Our innovative platform and trusted partnership enable our customers to connect communities, increase operational efficiency, and grow their business. For more information about AppFolio, visit appfolio.com.

Why AppFolio

Grow | We enable a culture of high performance, where delivering results is recognized by opportunities for growth and compelling total rewards. Our challenging and meaningful work drive the growth of our business, and ourselves.

Learn | We partner with you to realize your potential by investing in you from the start. We're cultivating a team of big thinkers through coaching and mentorship with our best-in-class leaders, and giving you the time and tools to develop your skills.

Impact | We are creating a world where living in, investing in, managing, and supporting communities feels magical and effortless, freeing people to thrive. We do this by innovating with purpose while cultivating a culture of impact. We learn as much from each other as we do our customers and our communities.

Connect | We excel at hybrid work by fostering an environment that feels flexible, personal and connected, no matter where we are. We create space to fuel innovation and collaboration, and we come together to celebrate, connect, and succeed.

Paddle as One.