About Zapier We're humans who simply think computers should do more work.
At Zapier , we’re not just making software—we’re building a platform to help millions of businesses globally scale with automation and AI . Our mission is to make automation work for everyone by delivering products that delight our customers . You’ll collaborate with brilliant people, use the latest tools, and leverage the flexibility of remote work. Your work will directly fuel our customers’ success , and as they grow, so will you.
Job posted: 5/12/2025
Location: Americas preferred
Hi there!
Are you ready to make a real impact in a dynamic and innovative environment? We're thrilled to invite you to join the Data AI/ML team at Zapier as a Senior Machine Learning Engineer!
As a member of our Data AI/ML team, you'll be at the forefront of our AI & Machine Learning initiatives. This is your chance to empower our product, business and engineering teams to leverage AI on a daily basis. You'll play a pivotal role in enhancing Zapier’s machine learning & AI tooling capabilities and influencing the way we build products using these tools. Your expertise will provide invaluable technical mentorship and assistance in scaling our use of AI/ML across the company.
Our Commitment to Applicants
Culture and Values at Zapier
Zapier Guide to Remote Work
Zapier Code of Conduct
Diversity and Inclusivity at Zapier
Zapier is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.
Even though our job description may seem like we're looking for a specific candidate, the role inevitably ends up tailored to the person who applies and joins. Regardless of how well you feel you fit our description, we encourage you to apply if you meet these criteria:
About You You have 7+ years of experience working with Machine Learning (ML) in production (with at least 1-2 years experience specific to Large Language Models (LLM)). You have experience writing clean Python code with reproducible results. You have knowledge of ML/LLM data structures and modeling, software architecture, libraries and frameworks to create models that sufficiently meet the needs of project goals.
You combine your strong applied ML/LLM knowledge with statistical expertise (e.g. confidence intervals, regression modeling, significance testing). You have strong mathematics skills, especially in statistics, to create algorithms. This includes demonstrated experience with common ML techniques for deep data mining and exploration (e.g. predictive modeling, time series modeling, classification, and clustering techniques). Understand how to determine the right machine learning algorithms for a given task and evaluate their performance, including understanding the trade-offs between different models and selecting the most suitable one based on the data and problem at hand.
You have a strong understanding of how LLMs and ML models succeed in a production environment. You have experience developing and improving upon evaluation frameworks for LLMs which focus on performance, reliability, and bias assessment/mitigation. You have extensive experience working with user data to engineer features for models, select appropriate model architectures, tune model parameters, and evaluate model quality. You have familiarity with fine-tuning models to achieve their maximum performance, i.e. optimizing hyperparameters, handling overfitting, A/B testing, and improving the efficiency of algorithms.
You’re familiar with various prompt techniques for LLM grounding such as chain-of-thought, static few-shot examples, and dynamic few-shot. You’re familiar with Retrieval-Augmented Generation (‘RAG’) systems. You have an understanding of how to optimize knowledge retrieval for improved model accuracy and speed. You can apply your knowledge of different indexing/chunking strategies on the data to achieve desired goals. You understand semantic search and vector databases, and how they differ from classic retrieval methods and databases. Experience with reranking and knowledge graphs is a plus.
You have a strong engineering sense. You’re familiar with automating ModelOps/DataOps processes which include creating pipelines and understand how CI/CD processes work. You’re a stellar data wrangler and have experience cleaning and structuring data for modeling purposes.
You are a skilled written communicator. Zapier is a 100% remote team and writing is our primary means of communication. You communicate complex technical topics clearly and in an approachable way.
You have proven stakeholder management expertise. As a collaborative thought partner, you're gifted at explaining your findings clearly to a non-technical audience. You have experience partnering with product and engineering to deliver business value through scalable ML/LLM development and deployment.
You enjoy collaboration and knowledge sharing. You appreciate our team’s values of eagerness to collaborate with teammates with any level of statistical and ML/LLM knowledge, iterating over your deliverables, and being curious.
You are an out of the box thinker. You employ your creative thinking skills to come up with new solutions and approaches that meet business objectives. You have sound problem-solving skills to refine prototypes and troubleshoot performance issues. You remain up to date on the latest innovations in machine learning in order to develop solutions that scale.
You understand that perfect is the enemy of good. You will default to action by initially shipping solutions that simply work and work simply while iterating as needed.
You’ve used AI tooling for work or personal use—or you are willing to dive in and learn fast. You explore new tools, workflows, and ideas to make things more efficient, and are eager to deepen your understanding of AI and use it regularly.
Things You’ll Do Zapier is a fast-growing and remote-first company, so you'll get experience on many different projects to support our stakeholders. Here are some things you might get to help our teams with:
Work with Engineering teams to develop and improve ML and LLM models, as well as refine our systems and processes in the space.
Design, implement, deploy, and improve upon prompting for LLMs with comprehensive evaluation suites to assess model performance and reliability.
Collaborate with other Data teams to develop ML projects in various sectors of the business.
Create LLM and ML model prototypes based on project specifications.
Process data for model fine tuning and fine-tune models for maximum performance that meet business needs.
Build and deploy data models as well as RAG systems.
Implement changes to algorithms to improve ML model performance as well as troubleshoot and address problems with deployed ML models to improve user experience.
Develop data literacy programs and provide easy-to-use tools with clear documentation, examples, and tutorials.
Participate in the on-call rotation (about 1 week per quarter) to support our production services.
Our stack is best summed up by: Databricks, AWS(S3), Python/Typescript, Airflow, dbt, Kafka, Braintrust.
Senior Machine Learning Engineer vs Other Roles At Zapier
How do we discern between a ML Engineer vs Applied AI Engineer? The following are discrete topics we expect to see a deep competency in specifically for ML Engineers:
Strong background in statistics.
ML techniques for deep data mining and exploration.
Automating DevOps/ModelOps/DataOps processes with pipelines and CI/CD.
Data wrangling and building data pipelines.
How to Apply At Zapier, we believe that diverse perspectives and experiences make us better, which is why we have a non-standard application process designed to promote inclusion and equity. We're looking for the best fit for each of our roles, regardless of the type of companies in your background, so we encourage you to apply even if your skills and experiences don’t exactly match the job description. All we ask is that you answer a few in-depth questions in our application that would typically be asked at the start of an interview process. This helps speed things up by letting us get to know you and your skillset a bit better right out of the gate. Please be sure to answer each question; the resume and CV fields are optional.
Education is not a requirement for our roles; however, if you receive an offer, you will need to include your most recent educational experience as part of our background check process.
After you apply, you are going to hear back from us—even if we don’t see an immediate fit with our team. In fact, throughout the process, we strive to never go more than seven days without letting you know the status of your application. We know we’ll make mistakes from time to time, so if you ever have questions about where you stand or about the process, just ask your recruiter!
Zapier is an equal-opportunity employer and we're excited to work with talented and empathetic people of all identities. Zapier does not discriminate based on someone's identity in any aspect of hiring or employment as required by law and in line with our commitment to Diversity, Inclusion, Belonging and Equity. Our code of conduct provides a beacon for the kind of company we strive to be, and we celebrate our differences because those differences are what allow us to make a product that serves a global user base. Zapier will consider all qualified applicants, including those with criminal histories, consistent with applicable laws.
Zapier prioritizes the security of our customers' information and is dedicated to adhering to all applicable data privacy laws. You can review our privacy policy here .
Zapier is committed to inclusion. As part of this commitment, Zapier welcomes applications from individuals with disabilities and will work to provide reasonable accommodations. If reasonable accommodations are needed to participate in the job application or interview process, please contact .
Application Deadline: The anticipated application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later, or if the position is filled.
Even though we’re an all-remote company, we still need to be thoughtful about where we have Zapiens working. Check out this resource for a list of countries where we currently cannot have Zapiens permanently working.
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