Senior Software Engineer, Machine Learning Infrastructure
Remote job description
A home is the biggest investment most people make, and yet, it doesn't come with a manual. That's why we're building the only app homeowners need to effortlessly manage their homes ?" knowing what to do, when to do it, and who to hire. With Thumbtack, millions of people care for what matters most, and pros earn billions of dollars through our platform. And as one of the fastest-growing companies in a $500B industry ?" we must be doing something right.
We are driven by a common goal and the deep satisfaction that comes from knowing our work supports local economies, helps small businesses grow, and brings homeowners peace of mind. We're seeking people who continually put our purpose first: advocating for pros and customers, embracing change, and choosing teamwork every day.
At Thumbtack, we're creating a new era of home care. If making an impact and the chance to do good inspires you, join us. Imagine what we'll build together.
Thumbtack by the Numbers
- Available nationwide in all 3,143 U.S. counties
- 70 million projects started on Thumbtack
- More than 4 million customers in the last 12 months
- Pros earn billions on our platform
- More than 8 million 5-star reviews for our stellar pros
- 1000+ employees and $3.2 billion valuation (June, 2021)
About the Machine Learning Infrastructure Team
At Thumbtack, our challenges span a wide variety of areas, ranging from building search, ranking & recommendations systems to optimizing pricing and spam detection models. The ML Infrastructure team is responsible for centralizing, standardizing and evolving machine learning infrastructure capabilities for teams across engineering that experiment with or deploy machine learning models for different problems. To read more about some of the engineering challenges at Thumbtack, visit our engineering blog.
Our ML team is in the middle of refining our future scale and enabling engineering and data science to rapidly deploy and solve complex problems. Our ML Engineers are experimenting to introduce growth and power new experiences.
- Collaborate with engineers, data scientists and product managers to identify shared ML infrastructure needs across areas like feature engineering, model experimentation, model inference & CI/CD, and model monitoring.
- Centralize and standardize ML infrastructure & associated best practices for product teams across engineering.
- When appropriate, experiment with and introduce next-generation ML infrastructure capabilities and frameworks so product teams can continue to harness the power of open source / vendor-driven advances in machine learning.
- Drive projects to completion with a tenacious focus on the business impact of those projects.
- Solve tough technical problems and stay up-to-date with the latest advances in this constantly evolving problem space.
If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.
- 5+ years of industry experience in engineering.
- 2+ years of industry experience working on machine learning modeling or infrastructure.
- You're fluent in at least one major programming language and would be able to switch between multiple languages. In our stack, we use Go, Scala & Python.
- You have experience building software on top of relational databases such as Postgres or MySQL.
- You can break down complex problems rigorously and understand the tradeoffs necessary to deliver great, impactful products.
- You're curious, you're data-driven, you love to ask questions, and you think critically about problems.
- You love delivering value to your users and your teammates through your work.
- You have experience building and evolving machine learning infrastructure.
- You have worked with frameworks like Tensorflow, Scikit, Airflow, AWS SageMaker.
- You have experience building and maintaining reliable, performant distributed systems.
- You're familiar working with major cloud providers and/or the big data ecosystem (Amazon Web Services, Google Cloud Platform, Hive, Spark, etc).
- You've demonstrated your ability to thrive in a fast-paced startup environment.
Thumbtack is a virtual-first company, meaning you can live and work from any one of our approved locations across the United States, Ontario or the Philippines. When it is safe to gather, we will begin to host in-person events on a regular basis. Remote employees will be expected to travel occasionally for these events to a Thumbtack library or offsite team-building location. In cities with 5+ employees, we are establishing local communities, where employees can gather for local events. Additionally, employees in the San Francisco, Salt Lake City, Toronto and Manila areas will have opt-in access to communal workspace at one of our Thumbtack libraries.
#LI-RemoteBenefits & Perks
- Virtual-first working model coupled with quarterly in-person events and Camp Thumbtack
- 20+ company-wide holidays including two week-long shutdowns
- Libraries (collaborative workspaces) in San Francisco, Salt Lake City, Toronto, and Manila
- Stipends for remote work support, home office set-up and internet
- Subscriptions and Employee Assistance Program for mental health and well-being
- Cell Phone Reimbursement, Thumbtack services (North America only)
Thumbtack is committed to working with and providing reasonable accommodation to individuals with disabilities. If you would like to request a reasonable accommodation for a medical condition or disability during any part of the application process, please contact email@example.com.
*Currently, Thumbtackers can live anywhere in Ontario or British Columbia, Canada or the Philippines or in any of the following US states: AZ, CA, CO, CT, FL, GA, HI, ID, IL, IN, KS, KY, MD, MA, MI, MN, MO, NE, NV, NH, NJ, NM, NY, NC, OH, OK, OR, PA, SC, TN, TX, UT, VA, WA, WI, Washington DC. Our long term vision is to hire across all of the United States and Canada, but this expansion will take a few years.
Company name: Thumbtack
Remote job title: Senior Software Engineer, Machine Learning Infrastructure
Job tags: Distributed Systems, airflow, AWS