Staff Machine Learning Engineer, Zapier
$245-367.4k
+ Equity + Bonus. Salary for UK candidates £140.1K-£210.1K. Salary for EU candidates €161K – €241.6K. Salary for Canada candidates CA$245K – CA$367.4K
More information about location
Workflow automation service
Job no longer available
Workflow automation service
501-1000 employees
Job no longer available
$245-367.4k
+ Equity + Bonus. Salary for UK candidates £140.1K-£210.1K. Salary for EU candidates €161K – €241.6K. Salary for Canada candidates CA$245K – CA$367.4K
More information about location
501-1000 employees
Company mission
Zapier's mission is to Make Automation Work for Everyone!
Role
Who you are
- 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
- 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
- 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
What the job involves
- 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 a fast-growing and remote-first company, so you'll get experience on many different projects to support our stakeholders
- 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
Application process
- Deadline to Apply: July 20, 2024 at 5:00 AM GMT+1
Our take
Even before remote working became the "in thing", freelancers, small business owners, and large organisations have found themselves needing more and more software platforms to serve their operational needs. As people used more software services, Zapier founders saw the need to connect the actions between these software and save everyone some time.
Zapier is the largest integration and automation tool for businesses. Since its founding, Zapier has grown its suite of automation offerings across almost every mainstream software service. The company is one of the most successful to come out of Y Combinator and has also been a pioneer of remote working.
Zapier has so far been able to capitalise heavily on its advantage as one of the first entrants and has had very little actual competition. Software services aren't going anywhere anytime soon, and organisations are only going to need more of them. This puts Zapier in a strong position for growth, but also opens up room for bolder companies to get in on the action. Companies like Airtable and Integromat are already preying on more niche segments of Zapier's market share.
Freddie
Company Specialist at Welcome to the Jungle
Insights
38% employee growth in 12 months
Company
Funding (2 rounds)
Oct 2012
$1.3m
SEED
Sep 2012
$0.2m
SEED
Total funding: $1.5m
Company benefits
- Work from anywhere
- Bonus program
- Unlimited vacation policy
- Great healthcare + dental + vision coverage*
- Retirement plan with company match*
- Stock options for every Zapien**
- 2 annual company retreats to awesome places
- 14 weeks paid leave for new parents
- Home office setup stipend
- Professional development allowance
Additional info
- As a fully remote company with 800+ team members across 40+ states, 38 countries, and 18+ timezones, we’ve adopted a culture of asynchronous work. This work style allows teams to collaborate effectively across locations, time zones, skills, and each individual’s energy levels, and empowers employees to work in a setting that fits their needs. In practice, we live on Slack, with most conversations in public channels. It mimics the open-office feel and allows everyone to search the chat logs if they need to find something that happened when they weren’t around
Leadership
Wade Foster
(Co-Founder & CEO)Prior to co-founding Zapier, wasEmail Marketing Manager with Veterans United Home Loans, and Customer Development Lead at The Idea Works.
Bryan Helmig
(Co-Founder & CTO)Was previously Product Dev/Manager at Veterans United Home Loans.
Mike Knoop
(Co-Founder)Was CPO and Head of Labs at Zapier before becoming President. Previously was a Graduate Research at the University of Missouri.
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