Zendesk Logo

Zendesk

Senior Machine Learning Engineer - Hybrid (San Francisco or Austin)

Reposted 15 Days Ago
In-Office
3 Locations
206K-308K Annually
Senior level
In-Office
3 Locations
206K-308K Annually
Senior level
Design, build, and deploy scalable ML and LLM solutions; own data pipelines, model development, deployment, and monitoring; collaborate with stakeholders to deliver measurable business impact and drive MLOps best practices.
The summary above was generated by AI
Job Description

Zendesk’s people have one goal in mind: to make Customer Experience better. 

The Enterprise Machine Learning team drives organizational value through scalable ML solutions and data-driven insights, fundamentally changing how business decisions are made. We collaborate closely with stakeholders, applying the latest advances in machine learning, deep learning, and large language models (LLMs) to create highly impactful outcomes. Our commitment is to advance the state of AI, statistical modeling, and robust system design to enhance and expand our core business capabilities.

Location

This position is open to candidates located within a commutable distance of our offices in San Francisco, Austin, or Madison. We are not considering fully remote applicants at this time.

Role Overview

As a Machine Learning Engineer, you will serve as a technical and strategic member within the team, driving the development and deployment of advanced data science and machine learning solutions—particularly those harnessing LLMs and deep learning. You will architect and scale ML systems, foster effective cross-functional collaborations, and ensure that business value is embedded in every technical decision. Your business acumen allows you to translate complex analytical approaches into actionable insights and stakeholder-friendly narratives, strengthening partnership and adoption across the enterprise.

Key Responsibilities
  • Drive the design, development, and deployment of advanced ML and AI solutions, with an emphasis on large language models (LLMs), deep learning architectures, and sophisticated statistical modeling.

  • Build scalable, robust data science systems—from data ingestion, data curation, data modeling to algorithm development, model deployment and monitoring—meeting enterprise-grade performance, reliability, and compliance standards.

  • Act as a subject matter expert, collaborating with data scientists, ML engineers, analysts, and business stakeholders to understand needs, define requirements, and deliver practical solutions with measurable business impact.

  • Effectively articulate complex technical concepts to non-technical partners, bridging gaps between technical teams and business operations for maximum results.

  • Drive adoption of best practices in MLOps, including CI/CD pipelines, containerization, orchestration, observability, and reproducibility.

  • Oversee and enhance the integrity, security, and compliance of all data science workflows and contracts.

  • Stay abreast of the latest industry advancements in ML, LLMs, deep learning, cloud data engineering, and MLOps solutions (AWS, Kubernetes, Snowflake, etc.).

  • Fostering technical excellence and ensuring alignment with business objectives.

What We’re Looking ForEducation & Experience:
  • 3+ years’ experience in Data Science, Machine Learning, or a related field

  • BA/BS in Computer Science, Data Science, or related discipline (advanced degree is highly preferred)

Technical Expertise:
  • Deep expertise in statistical modeling, machine learning, and deep learning (including practical experience with LLMs and transformers)

  • Strong programming skills (Python preferred; Java, Scala, or similar also valued)

  • Proven ability to build and optimize scalable data science solutions—end-to-end—from data pipelines (dbt, Astronomer, Snowflake, AWS) to deployment and monitoring (Docker, Kubernetes, CI/CD, MLOps best practices)

  • Experience handling and analyzing large datasets, with a preference for experience in cloud data warehouses (Snowflake)

Business Acumen:
  • Demonstrated success in translating business needs into analytical solutions, driving quantifiable impact

  • Strong stakeholder engagement skills, with a track record of building trusted business partnerships and driving adoption of data science initiatives

Communication & Collaboration:
  • Exceptional ability to simplify and communicate complex data science concepts to technical and non-technical audiences alike

  • Experience working cross-functionally with engineers, analysts, and product leaders

  • Steadfast commitment to continuous learning, collaboration, and fostering an inclusive, innovative team environment

Why You’ll Thrive Here
  • Opportunity to develop and scale of LLM and deep learning solutions with real-world business impact

  • An environment that values innovation, ownership, and professional growth

  • The chance to work on high-visibility, high-impact projects at scale alongside a passionate multidisciplinary team

#LI-JH1

The US annualized base salary range for this position is $206,000.00-$308,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.

Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.

The intelligent heart of customer experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [email protected] with your specific accommodation request.

Top Skills

Astronomer
AWS
Ci/Cd
Dbt
Deep Learning
Docker
Java
Kubernetes
Large Language Models (Llms)
Mlops
Python
Scala
Snowflake
Statistical Modeling
Transformers
HQ

Zendesk San Francisco, California, USA Office

989 Market St., San Francisco, CA, United States, 94103

Similar Jobs

16 Days Ago
Easy Apply
Remote or Hybrid
2 Locations
Easy Apply
160K-200K Annually
Senior level
160K-200K Annually
Senior level
Artificial Intelligence • Big Data • Computer Vision • Information Technology • Machine Learning • Analytics • Defense
As a Senior Machine Learning Engineer, you will develop machine learning models, automate data pipelines, and collaborate with teams to meet customer needs.
Top Skills: AngularC++DockerGoGraphQLJavaKubernetesPythonPyTorchReactRestRustScalaScikit-LearnTensorFlowVue
16 Days Ago
Easy Apply
In-Office
Austin, TX, USA
Easy Apply
Mid level
Mid level
Information Technology • Robotics
The Machine Learning Engineer will develop and optimize models, manage datasets, enhance training pipelines, and collaborate across teams to innovate in autonomous vehicle technology.
Top Skills: C++JaxNumpyPysparkPythonPyTorchScipySQLTensorFlow
8 Minutes Ago
Easy Apply
Hybrid
Austin, TX, USA
Easy Apply
60K-70K Annually
Entry level
60K-70K Annually
Entry level
eCommerce • Fintech • Food • Mobile • Social Impact
The Account Recovery Associate monitors partner account health, manages delinquent balances, ensures smooth recovery workflows, and collaborates across teams to maintain accurate records.
Top Skills: Accounting SystemsCRMExcelHubspotSalesforce

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account