Job details

Staff Machine Learning Engineer

Job Posted: 6/20/24

Location: North America or EMEA

Hi there!

Are you ready to make a significant impact in a dynamic and innovative environment? We’re thrilled to invite you to join the Data AI/ML team at Zapier as a Staff Machine Learning Engineer!

As a senior leader of our Data AI/ML team, you’ll drive our AI & Machine Learning initiatives to new heights. This is your opportunity to empower our product, business, and engineering teams to leverage AI on a daily basis. You’ll play a critical role in enhancing Zapier’s machine learning & AI tooling capabilities and setting the strategic direction for how we build products using these tools.

You will support engineers and embedded data scientists across Zapier’s products, directly helping to build some of our AI-enabled user features.

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 10+ years of experience working with Machine Learning (ML) in production environments, with demonstrated hands-on experience specific to Large Language Models (LLM). You excel in writing clean, maintainable Python code with reproducible results. Your deep understanding of ML/LLM data structures, modeling, software architecture, libraries, and frameworks allows you to create models that effectively meet project goals.
You have a strong engineering background. You have 7+ years of experience with automating MLOps/DataOps processes which include creating pipelines, developing CI/CD and building out different ways to serve ML models for product use cases. You’re a stellar data wrangler and have experience cleaning and structuring data for modeling purposes.
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 setting evaluation standards for ML/LLM models across organisations, which focus on performance, reliability, and bias assessment/mitigation. You have experience designing reusable data feature stores, reusable model architectures and data pipelines. You have experience creating and deploying guidance & systems for your organisation about how approach different aspects of ML lifecycle (eg. optimizing hyperparameters, handling overfitting, A/B testing, and improving the efficiency of algorithms).
You are aware of the established developments in the LLM world, including the use cases in which their use is appropriate (such as various prompt techniques for LLM grounding or Retrieval-Augmented Generation (‘RAG’) systems). You have set up semantic search and/or vector databases, and understand best practices to make them work effectively. Experience with reranking and knowledge graphs is a plus.
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.

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:

Guide Engineering teams into how to best leverage ML and LLMs to create user value within our product or increase the value created by existing systems and processes.
Design, implement and rollout best practices for LLMs for different use cases, including prompting, fine-tuning and evaluation suites.
Enable other Data teams to add more value faster across the business, through reusable tooling and education.
Identify large value opportunities for LLM and ML across the business, create model prototypes to address those opportunities.
Scope data modeling and infrastructure needs for effective fine-tuning of models for maximum performance that meet business needs.
Build and deploy tooling that let’s other teams build ML systems faster. This might include reusable vector databases, RAG systems, serving pipelines or evaluation suites.
Consult on existing ML systems, recommending changes to algorithms to improve ML model performance as well as troubleshoot and address problems with deployed ML models to improve user experience.
Design and lead creation of data literacy programs and provide easy-to-use tools with clear documentation, examples, and tutorials.

Our stack is best summed up by: Databricks, AWS(S3), Python, Airflow, dbt, Kafka, Looker and R.

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 education or 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.

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 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 jobs@zapier.com.

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.

Zapier Glassdoor Company Review

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