Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.

Flyte

Hi Flyte community! :wave:

I’m <https://www.linkedin.com/in/goodgravy/|James>, Head of Engineering at Elicit (I’ve also led/advised ML &amp; Engineering teams at Outschool, Spring, and Square). Posting here because I’m excited to be hiring Elicit’s first Data Engineer!

<https://elicit.com/welcome|Elicit> is an AI research assistant built for professional researchers and high-stakes decision makers. Instead of just producing LLM slop in a chat bubble, Elicit helps users break down hard questions, gather evidence from scientific/academic sources, and reason through uncertainty.

We use *Flyte* and PySpark to orchestrate our ML pipelines that process a couple hundred million academic/research papers: you will initially own and improve this infrastructure. Moving on from there, you’ll figure out how we can scale our data platform to ingest other structured and unstructured documents, spreadsheets and presentations, and rich media like audio and video. We also need your help with ML-adjacent tasks like preparing datasets for fine-tuning our models. Big picture, your work will help accelerate data ingestion, enable secure enterprise integrations, extend Elicit to work over any kind of data corpus, and more.

We’re a small Series A company (about 20 people so far), building AI systems that push the boundaries of how LLMs can be useful. We’ve been thinking about harnessing powerful AI since even before GPT-1 was trained. We need engineers who care about making AI more useful, trustworthy, and aligned with how people actually make tough decisions.

I’ll add more information about Elicit in the thread. If you're interested in applying your Flyte expertise to help build AI systems that accelerate scientific progress, please check out the <https://elicit.com/careers?ashby_jid=4617f630-f971-4716-b753-2915ce9c04a7&amp;utm_source=flyte-slack|job description>—I’m happy to answer any questions or discuss how we’re utilising Flyte in our stack!

Best,
James

IMO, here’s why Elicit stands out:
• *Structured, Inspectable Reasoning:* Our approach to building powerful ML systems is to focus on the _<https://ought.org/updates/2022-04-06-process|process>_<https://ought.org/updates/2022-04-06-process| not the >_<https://ought.org/updates/2022-04-06-process|outcome>_. Users can view and critique reasoning at any stage of the process.
• *Cited, Verifiable Evidence*: Claims are extracted from documents reports, and we link back to these sources so users can verify and interpret them in context. 
• *Tailored to Experts:* Elicit is already used by forecasters, researchers, and decision-makers who demand rigour—they help keep the bar high for reliability and product design. 
• *Custom Evaluation Infrastructure:* We’ve built our own eval tools focused on reasoning quality, source fidelity, and epistemic soundness—not just raw model scores.
• *Cautious of AGI, without the DOOM*: We're optimistic that powerful AI can be an amazing thing for the world, while recognising that it could also be disruptive or harmful. Join us to help bend progress towards positive outcomes!
I love that our work centres problems that don’t yet have best practices—like creating new evaluation metrics, building human-in-the-loop workflows, and translating fuzzy human questions into structured model behaviours. It’s challenging but incredibly fulfilling—I’d love to hear from you if this sounds like something you’d be interested in.

Hi <@U08STEAQXGS> 

If this role hires remotely in India, I am interested in this opportunity

Only open to people in US timezones I'm afraid <@U08T13CGWCU> :confused: