About Us
At iterative.ai, we build open-source tools for machine learning DVC (12k+ ⭐ on GitHub), and enterprise-grade data infrastructure solutions. We also offer a team collaboration SaaS solution - Studio. We're a well-funded (Series A), remote-first team (50+ employees) on a mission to solve the complexities of managing datasets, ML infrastructure, ML models lifecycle, and other ML & data-centric workflows.
We value great collaboration and communication skills, both among internal teams and in how we interact with our users. We take care to balance and be responsive to the needs of our open source community as well as our enterprise customers.
Check us out in other places:
🖥 Website 📂 Docs 👾: GitHub 🖊 Blog ⏯️ YouTube 💬 Discord
Job Description
Participate and lead efforts around the development of our flagship DVC product and ecosystem - including leading and owning cross product features and efforts and strong involvement with adjacent projects and products.
We expect strong SW engineering skills and knowledge and excellent coding culture (CQ standards, automation, testing, FOSS contributions, etc). Specifically Strong Python experience is required, as well as and experience building dev-tools and maintaining open source software.
Responsibilities
- Discuss, research & lead issues, features, and even products.
- Be 100% hands on, be able to drive large changes, hold brainstoring and architecture discussions and put technical spec in place for other members to collaborate and follow on
- Write (lots of) code (see some PR examples).
- Write docs for your code (see this repo).
- Write blog posts and public updates about features and engineering challenges - participate in the product work lifecycle
- Work directly with management and founders and help translate our vision into a working, delightful functionality
- Be actively involved in the community - Support: talk to users on Github, Discord, forum, Understand their workflows: work with users, customers, product. Be able to demo and mock user projects and understand the hardships of ML and data-centric workflows
Requirements
- Motivation and interest - devtools space, Machine Learning and Data science space, Python ecosystem, storage and data systems
- Remote work self-discipline
- Excellent communication skills - clear, constructive, and respectful dialog with other team members, community and leadership. This includes (but not limited to) - written communication in form of technical discussions in various systems. We feel most at home on: Github, Slack, and Notion.
- Ability to manage your time, define, spec-out and deliver large tasks and features. contribute and co-own team and product planning, respect deadlines business priorities (demos, customers, conventions, and other milestones), etc
- Experience working remotely in Agile and dynamic teams
- Open source contributions and experience in maintaining projects (OSS)
- System programming experience - kernel-level, virtualization, databases, filesystems, etc.
- Strongly prefer: Some Machine Learning or Data Science experience - this is so you can easily identify and replicate user issues and worklows
ℹ️ Our Hiring Process
We will go over the process with you in the Introductory call to make sure it is clear and you know what to expect.
Here is the full interview process you can expect - It’s our go-to for most positions:
🤙 Introductory call [~1h]
👨🏫 Tech call with a team member [~45m]
👩🏾💻 Take-home coding task [real-world, asynchronous] - We pay for your time! See this FAQ.
🦾 Task summary / retro call [Optional, ~1h]
✏️ Offer
👩💻 Culture - We take care of our people
💖 Diversity - As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, iterative.ai is the type of company where you can balance great work with great life, and work with a wonderful team that does the same! No matter who you are or where you’re from; we need you for what you can do and for caring about ML and delivering great developer tools!
⚖️ Equal opportunities - We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do. No country or region takes precedence for personal growth, compensation, team recognition, or anything else, it just doesn’t matter where you are.
👣 Flexibility first - Ability to craft your calendar with flexible locations and schedules
⚓️ Team Driven Culture - Engineering team is involved in product discussions and planning. We do it openly via GitHub or Discord chat. Well-defined process that we all participate in improving. As an employee you will have visibility to everything in Iterative, we are One team.
👏 Perks & Benefits
🌎 Work wherever you want - No offices. Team is distributed remotely worldwide.
🗓️ Work whenever you want - Asynchronous communication and engineering culture. We are light on meetings and emphasize people finding their own schedule to be prolific & effective. Oh yeah, also Unlimited PTO and sick days!
🤗 Open-source your code - We’re an open-source-first company (frankly, it’s in our DNA). Your work will be visible and will be used by thousands of developers every day! Check out our Discord and GitHub.
🪙 Competitive compensation - based on the work you do here and not your previous salary.
⚕️ Great health coverage (medical, dental, vision) for you and your family, 100% paid by us (US only, but can discuss and reimburse, adjust the salary in other locations).
🛡️ Benefits - 401K with 100% match up to 4% of annual salary (US only, but we give the best we can worldwide through reimbursements and hiring platforms).
🎤 Participate in conventions and conferences (PyCon, PyData, O'Reilly AI, etc) - We encourage and support everyone in giving talks, writing blog-posts, and other activities.
Top Skills
What We Do
We build DVC, CML, and other developer tools for machine learning. We're a well-funded, remote-first team on a mission to solve the complexity of managing datasets, ML infrastructure, ML models lifecycle management. Iterative brings best engineering practices to data science and machine learning.