We build a high-performance model development environment that enables ML engineers to train better models more quickly, to seamlessly utilize and manage large GPU clusters, and to collaborate more easily with their teammates. Determined allows ML engineers to focus on doing ML at scale, rather than managing infrastructure or writing boilerplate code.
We work at the intersection of large-scale distributed systems and cutting-edge machine learning. Our customers are highly skilled ML engineers and domain experts working on exciting problems in biotech, hardware design, autonomous vehicles, and more. We interact with them to learn more about their data sets, modeling problems, and infrastructure, to help them with our product, and to improve our product offering.
After 4 years as a startup company, we were recently acquired by Hewlett Packard Enterprise (HPE). At HPE, we will remain a distinct organization — we'll be building the same product targeting the same users. Plus we'll have access to HPE's customers, hardware products, and resources to take our mission to the next level.
Applied Machine Learning Engineer San Francisco, CA, United States or Remote
ML Developer Advocate San Francisco, CA, United States or Remote
Senior Technical Support Manager Remote
Software Engineer, Backend Systems San Francisco, CA, United States or Remote
Software Engineer, Front-End San Francisco, CA, United States or Remote
Why join us?
We value inclusiveness, mentoring, and life-long learning. We believe the best ideas can come from anyone and anywhere, and we have to be humble enough to listen for them. We are customer-focused, but don't think the customer is always right. We are excited about the latest in ML and distributed systems research but try to implement the minimum valuable product. We believe in open communication and transparency in our process and priorities.
In any gold rush, it's good to be a miner but it's better to be the one selling the shovels. There is an deep learning gold rush going on now (NVIDIA projects $50B in data center revenues by 2023). The existing tools (TensorFlow, PyTorch, etc) are great but don't address the problems ML teams face when they try to scale. We are building those tools so every company can benefit from the AI revolution, not just the FAANGs of the world.
As part of HPE, we're able to offer some of the best benefits of both a high-growth startup and a more established company. We're still growing rapidly, and we're still focused on building the same product and making our open-source community successful. We now also have the financial stability of one of Silicon Valley's most iconic companies, and the ability to sell Determined to the countless organizations that rely on HPE as a hardware/IT vendor.
Engineering at Determined AI
We have one product and one team, where everyone is a worker-leader. We combine input from customers, engineers and company leadership to prioritize our work, and work hard to make decisions transparent. We believe in tight feedback with customers, and in minimum valuable products.
We believe in just enough (but not too much) process; currently we run scrum with two week sprints. We use Github to manage our work; we require code review, lint, and tests to pass for all our PRs. We run an extensive continuous integration pipeline to test our GPU features. We use Slack, GSuite and have provisioned a video conferencing system for our remote workers.
We have implemented, from scratch, a distributed, fault tolerant GPU cluster manager and scheduler, purpose-built for DL and ML workloads. We have invented, published and implemented state-of-the-art hyperparameter optimization algorithms in our platform. We have numerous other research ideas ready to turn into product features that will differentiate us from our competitors.
Our customers are highly skilled ML engineers and domain experts working on exciting problems in biotech, hardware design, adtech and more. We interact with them daily to learn more about their data sets, modeling problems, and infrastructure, to help them with our product, and to improve our product offering.
Implement state of the art communication strategies for distributed training of deep learning models.
Research and implement novel resource-aware model optimization strategies to help customers deploy models to resource-constrained environments.
Work with customers to understand their workloads, help them find improved performance using our platform, and champion and implement new product features to improve their experience.
Explore interesting new data visualizations in our web UI to help customers understand their experiments and workloads.
Working at Determined AI
We believe the best ideas can come from anyone and anywhere, and we have to be humble enough to listen for them. We are customer-focused, but don't think the customer is always right. We are excited about the latest in ML and distributed systems research but try to implement the minimum valuable product. We believe in open communication and transparency in our process and priorities. We believe in the healing power of karaoke and hot sauce.
We had our first retreat last summer in sunny Santa Cruz, where we took stock of our progress, brainstormed new ideas, did a hackathon, played mini-golf, and otherwise had a great and enriching time.
We've given many conference talks so far, our founder is the organizer of the SysML conference, one of our advisors is an organizer for O'Reilly, so we have lots of conference participation in our future.
Our CEO, CTO and VPE all have young children, we are family-friendly and flexible.
We have an informal in-house talk series where our staff can talked about things they know about: search engines, bread baking, robot-battling, CS:GO and more. We had an office-warming party with a hot sauce challenge, and a fundraising party is imminent. We've had board game nights and most importantly have a karaoke-positive culture.
Work from Home
We allow work from home and have remote staff. We have worked hard to make sure they remain connected with the company and team.
Full health, vision and dental coverage, flexible spending accounts for dependent care, medical, and commute costs.
We offer a 401k plan (no employer match).
We offer reimbursement of some gym membership fees.
We have a flexible vacation policy; we actively encourage employees to maintain a healthy work/life balance.
Interested in this company?
Skip straight to final-round interviews by applying through Triplebyte.