Immunera | Principal Machine Learning Engineer | NYC area (hybrid) | Full-time | immunera.ai
Hey! I’m Maxim, cofounder/CEO of Immunera.
We're building blood tests that use gene sequencing and machine learning to help patients with autoimmune disease. Immunera spun out of years of research at Stanford, and our technology has been published in Science and covered by The New York Times.
We're hiring a Principal Machine Learning Engineer to shape the core models and infrastructure that power our blood tests. We are partnering with hospitals to generate training data from real patients for our language models and other biological sequence models.
This is a senior engineering role with significant autonomy at an early-stage, venture-backed startup. We're looking for strong experience building and operating ML systems in production (Python, PyTorch/TensorFlow, cloud platforms). Prior biology or healthcare experience is NOT required; we care much more about your ability to reason about data, models, and systems.
Immunera | Principal Machine Learning Engineer | NYC area (hybrid) | Full-time | immunera.ai
Hey! I’m Maxim, cofounder/CEO of Immunera.
We're building blood tests that use gene sequencing and machine learning to help patients with autoimmune disease. Immunera spun out of years of research at Stanford, and our technology has been published in Science and covered by The New York Times.
We're hiring a Principal Machine Learning Engineer to shape the core models and infrastructure that power our blood tests. We are partnering with hospitals to generate training data from real patients for our language models and other biological sequence models.
This is a senior engineering role with significant autonomy at an early-stage, venture-backed startup. We're looking for strong experience building and operating ML systems in production (Python, PyTorch/TensorFlow, cloud platforms). Prior biology or healthcare experience is NOT required; we care much more about your ability to reason about data, models, and systems.
Hi @zeagle, sorry to hijack the thread (didn’t see a way to DM you)
I'm a PhD student working on a new lupus diagnostic blood test approach [1]. Hoping to steer the project towards true clinical needs.
I'd love to ask for your feedback as a technologist + rheumatologist on a few lupus + RA diagnostic directions we're considering. Would they actually be useful in your practice?
Would you be open to a quick chat? My email is maximz@stanford.edu.
Love this. I appreciate your building on ripgrep versus my own bulky lucene-based approach a while back (https://github.com/maximz/sift), and that you don’t require pre-indexing but build up a cache as you go.
I may have what you're looking for: I've been working on exactly this problem, because I grew tired of the headaches from maintaining a "snowflake server" (http://martinfowler.com/bliki/SnowflakeServer.html), which I configured once in the past and would be very difficult to reproduce.
Here's a super-simple Docker host stack I put together that you can install on a cloud machine fairly easily. It runs Docker containers, does automatic backups, and has monitoring and alerting built-in. I've run around 5 webapps, split between 10 containers, on this infrastructure for about 6 months with significantly fewer headaches. Monitoring alerts go straight into a personal Slack channel.
The implementation is deliberately low-level -- you'll be running bare docker commands -- because the goal is to have a trivial infrastructure and to learn Docker in the process. There's no reliance on the "magic" in big wrappers like Kubernetes. Because there's nothing fancy in here, it's simple to understand and use.
My write-up is rough around the edges right now, but eventually this will turn into a simple blog post with an Ansible playbook attached. Here's a rough draft of how to set it up manually: https://github.com/maximz/docker-host/blob/master/public_doc...
There's an nginx reverse proxy fronting the Docker containers. You can do a zero-downtime deploy pretty easily. Happy to answer any questions if they arise.
I saw David Donoho give this talk live in September at Princeton's Tukey Centennial conference -- fantastic, and well worth a read. IIRC, gives a good history of data analysis, how to think about the different definitions of and roles for data science, and an introduction to Tukey's work.
For more on the history of data science, here are references from a similar talk by Chris Wiggins: http://bitly.com/icerm
I think this is because of different risk preferences, which make the conclusion obvious.
These teens have higher risk preferences. Entrepreneurship is a high-risk, high-reward endeavour.
Since we count only the successful ones, those who take higher risks and are successful naturally are more successful than those who take smaller risks.
Hey! I’m Maxim, cofounder/CEO of Immunera.
We're building blood tests that use gene sequencing and machine learning to help patients with autoimmune disease. Immunera spun out of years of research at Stanford, and our technology has been published in Science and covered by The New York Times.
We're hiring a Principal Machine Learning Engineer to shape the core models and infrastructure that power our blood tests. We are partnering with hospitals to generate training data from real patients for our language models and other biological sequence models.
This is a senior engineering role with significant autonomy at an early-stage, venture-backed startup. We're looking for strong experience building and operating ML systems in production (Python, PyTorch/TensorFlow, cloud platforms). Prior biology or healthcare experience is NOT required; we care much more about your ability to reason about data, models, and systems.
Full JD: https://www.immunera.ai/jobs
Contact: maxim@immunera.ai (subject: “HN ML job”)
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