Software Engineer (AI Data Engine, Staff/ Senior, Open Source, SaaS)

Posted 15 Hours Ago
Remote
Senior level
Software
The Role
The Software Engineer will be responsible for developing large new areas within data management software, handling the entire product lifecycle, and ensuring high reliability of system software. This role demands experience with AI infrastructure at scale and solid Python knowledge. Multi-tasking and quick adaptation to new technologies are essential.
Summary Generated by Built In

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


"... competitive advantage in AI goes not so much to those with data but those with a data engine: iterated data acquisition, re-training, evaluation, deployment, telemetry. And whoever can spin it fastest. " - A. Karpathy


We are building the next generation of DVC - DVCx that will serve as a core infrastructure component to manage large amounts of unstructured data (e.g. on a scale of the LAION 5B dataset). How to create or improve a dataset in minutes if there are millions or billons of objects in a bucket? How to add additional signals (e.g. embeddings) at scale to a dataset like LAION 5B?


Join us if you have experience in building big-data, distributed data processors (Spark, Ray, etc), if you have experience using data infrastructure like the one that is used in self-driving cars, if you have similar experience and you want to make this unstructured data management tools available in open source and SaaS.

Responsibilities

  • Own large new areas within our data management software, and build them from ground up
  • Participate in the entire product lifecycle from concept through production
  • Be able, and willing, to multi-task and learn new technologies quickly

Must Have

  • 5+ years of industry experience as a software engineer
  • Experience building or working with AI infrastructure at scale (similar to Tesla's data engine, Waymo, etc) or similar relevant experience
  • Solid knowledge of Python
  • At least one year of experience with file systems, concurrency, multithreading, and server architectures
  • Passionate about building highly reliable system software

Great to Have

  • Experience working remotely
  • Experience working on high performance database internals, or heavily distributed server backends
  • Prior startup experience
  • Experience at other API technology companies
  • Command of modern system-level languages like Go or Rust

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

Go
Python
Rust
The Company
HQ: San Francisco, CA
60 Employees
On-site Workplace
Year Founded: 2018

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.

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