Email Alert for
ⓘ There was an unexpected error processing your request.
Please refresh the page and try again.
If the problem persists, please contact us with your issue.
You can always manage your preferences and update your interests to ensure you receive the most relevant opportunities.
Get ready to discover your next great opportunity.
Scribe
San Francisco, CA, United States
About us Scribe is where exceptional people come to do the best work of their careers. We are a Series A, product-led growth startup based in San Francisco. We help over 1 million go-to people document and share what they know. Scribe automatically creates step-by-step guides for any process, putting an end to hours spent taking screenshots and ru
Job Source: ScribePerplexity AI
San Francisco, CA, United States
Perplexity is building the next generation answer engine, empowering our users to find information in new and more effective ways. Perplexity applies LLMs for knowledge search at scale, serving millions of users across the world. In pursuit of this mission, we are looking for engineers to build recommendation systems for a more engaging, easier to
Job Source: Perplexity AIThe Learning Experience #398
San Francisco, CA, United States
At OSARO we develop solutions to endow industrial robots with the level of autonomy needed to perform an unprecedented variety of complex pick and place tasks leveraging sophisticated robot control and neural network-based perception algorithms. You are a good fit if you are passionate about what you build, you feel a strong sense of ownership, and
Job Source: The Learning Experience #398Job Board
San Francisco, CA, United States
By making evidence the heart of security, we help customers stay ahead of ever-changing cyber-attacks. Corelight is a cybersecurity company that transforms network and cloud activity into evidence. Evidence that elite defenders use to proactively hunt for threats, accelerate response to cyber incidents, gain complete network visibility and create
Job Source: Job BoardThe Learning Experience #398
San Francisco, CA, United States
Job Requisition ID # 24WD78712 Digital Experience & Customer Empowerment Machine Learning Team (DXC-ML) @Autodesk The DXC-ML Team is responsible for delivering Machine Learning features that enhance the customer experience for Sales, Marketing, and Customer Success functions at Autodesk. We aim to help our customers through conversation, person
Job Source: The Learning Experience #398Cascading AI
San Francisco, CA, United States
Casca is on a path to deploy enterprise AI agents at scale to automate complex tasks in the modern banking system. As an ML Engineer, you will see your work repeatedly shipped to automate 1000s of real world conversations, helping small businesses get funding. What you'll do: Contribute rapidly to our core software platform that automates the lendi
Job Source: Cascading AIPicnicHealth
San Francisco, CA, United States
[Full Time] Machine Learning Engineer at PicnicHealth (United States) | BEAMSTART Jobs Machine Learning Engineer PicnicHealth United States Date Posted 17 May, 2023 Work Location San Francisco, United States Salary Offered $150 — $185 yearly Job Type Full Time Experience Required 6+ years Remote Work Yes Stock Options No Vacancies 1 available
Job Source: PicnicHealthTavus
San Francisco, CA, United States
[Full Time] Machine Learning Engineer at Tavus (United States) | BEAMSTART Jobs Machine Learning Engineer Tavus United States Date Posted 11 May, 2023 Work Location San Francisco, United States Salary Offered $125000 — $170000 yearly Job Type Full Time Experience Required 3+ years Remote Work Yes Stock Options Yes Vacancies 1 available Backed
Job Source: TavusSan Francisco, CA, United States
While significantly more efficient than humans for many tasks, the cost and latency of LLMs is still prohibitive for most real world applications.
At Ntropy, our mission is to make LLMs viable at scale. We are developing a new kind of domain-specific wrappers for language models, that leads to a reduction in the number of queries to the base model by 3-5 orders of magnitude and cost per datapoint by 2-3 orders of magnitude, without impacting accuracy.
The first domain we have been building for is finance.
In early 2022, we released the first set of tools for extracting information from bank transactions. This challenge has traditionally demanded human expertise—accountants, underwriters, financial controllers, which restricted applications to only the most substantial transactions and left areas like small business lending and instant consumer credit scoring out of reach.
We
come from various fields - engineering, mathematics, physics, and arts.
are allergic to over-engineering.
are anarchists at heart and like to hack around the status quo.
love playing board and video games.
are radically honest and appreciate challenging one another, rather than giving out “pats on the back”. Yet, we can always rely on each other for support, feedback, and results.
are willing to learn and adapt quickly to new situations and requirements. Languages, frameworks, libraries, compilers, etc. are just tools for a job. A new problem might need a new tool. If it doesn’t exist yet, we will build it.
have a sense of humor (well, we think we do).
As an early member of our ML team, you will help
build in-house LLMs and domain-specific caching infrastructure that outperform the largest foundation models on real-world tasks and make them viable at 100M+ requests per day.
build the team and drive the direction of the company.
shape our product and culture.
experience the real-world impact of what you build.
The following are a big plus
fluency in Python and Pytorch.
experience with training and deploying models in multi-GPU environments.
past projects in LLMs, VLMs, embeddings models, RAG.
recognized open-source contributions.
participation in competitive programming events (Putnam, IOI, IMO, Kaggle, etc.).
FAQ
Where is Ntropy located?
We are currently starting our SF office and are hiring there for in-person roles only. We also have hubs in London, UK and Lisbon, Portugal.
Do you consider part-time work?
Not at the moment. Full-time roles only.
How are you funded?
We are backed by some of the top funds in the world and have raised double-digit millions of dollars so far. We can share more details over the call.
Do you already have a product and customers?
Yes. We have been in production since 1st Jan, 2022 and have in the high double digits customers using our APIs in production.
How big is your team?
We are around 20 people at the moment. Mostly engineering and product.
What is the interview process like?
Send us an overview of problems you have encountered before and how you approached solving them. Please include as much detail as possible: code, algorithms, derivations, proofs, etc. We will then do a video call to kick things off and go through it (45 mins).
We will give you a take-home project related to whatever we are currently working on (3-4 hours). Alternatively, if you have a relevant project that you worked on previously that demonstrates your skills as an engineer, you are welcome to use that instead.
We will then do a deep-dive through the project over a call and discuss the implementation, improvements, and bottlenecks.
Above all, we respect your time and commitment and will keep you up to speed on where we are at during the whole process.
What are your hiring plans?
We expect to be 40-50 people by the end of 2024.
What is your current stack?
backend - Python, Rust
compute - AWS, GCP
ML - PyTorch, ONNX, Triton, LLMs
Work / life balance
We are a startup which requires you to put in a lot more work and soul than a regular job. We believe, however, that nothing easy is worth doing. We will expect a lot from you, and you should expect a lot from us.
What is the compensation?
approx. $130-200k • 0.1-0.3%
#J-18808-Ljbffr
Email Alert for Machine learning engineer jobs in San Francisco, CA, United States
ⓘ There was an unexpected error processing your request.
Please refresh the page and try again.
If the problem persists, please contact us with your issue.
You can always manage your preferences and update your interests to ensure you receive the most relevant opportunities.
Get ready to discover your next great opportunity.