Coral Genomics is actively seeking a Senior Machine Learning Engineer to join their team through our Bioinformatics program.
More about the role
More about the program
Truly innovative genetic techniques that reduce the cost of clinical genetic testing by 100x.
Strong progress: already started commercial pilots, going through CLIA certification, on track to raise Series A and start helping first patients.
Strong venture-backing from top investors like Y Combinator, Sequoia Capital, and 8VC.
Coral is currently 7 people, seed stage, and headquartered in San Francisco.
Current drug development process suffers from diversity bottlenecks.
The Lack Of Human Diversity
There are over 7 billion people in the world, and they respond differently to different drugs because they have different genetic compositions. However, only up to 3000 people are tested during clinical trials. As a result, most drugs only work on 10% - 50% of the population, and we don't know which 10% - 50%.
Clinical trials lack human diversity both in the sense that women and ethnical minorities are underrepresented, and that even if everyone is proportionally represented, the absolute number of people in clinical trials is simply too small to capture the genetic diversity of the entire population.
The Lack Of Therapeutic Diversity
On the other hand, the number of drugs that can be given to a patient starts out as infinity. This number reduces with each step along the way to get FDA approval.
Today, it is impossible to test large numbers of drugs across large numbers of people, to find which ones are the best treatment for an individual patient.
Coral Genomics' Product & Vision
Coral has developed its own novel genetic sequencing techniques to solve the diversity bottleneck problem. Their new techniques make it possible to test how cells from different patients respond to different drugs in a timely and cost-effective way.
They have already built one of the world's largest databases functionally associating genetic variations to drug response and clinical outcomes.
In terms of product, Coral works with healthcare systems to provide end-to-end precision medicine support from next-generation sequencing to patient/provider facing healthcare reports. Fueled by their large diverse dataset, Coral's predictions have higher accuracy rates across age, gender, and race, and are more affordable & higher margin than any competitors.
Coral envisions a future where people's genetic information is in their electronic health records, and treatment for every disease is guided by predictions that harness the genetic diversity of the entire population.
The motivation for building Coral originated when Atray's family member Inflammatory Bowel Disease (IBD). For IBD patients, there are multiple drugs and treatments, many of which have intense side effects. For a patient, there is no way of knowing if a drug will work for them without actually trying it. For 20% to 40% of the patients, no drugs work and they have to go through surgery in the end.
Atray has witnessed firsthand what it was like to go through this process, where his family member tried a drug that only works for 50% of patients, waited for 6 months, and if the drug was not working restart this cycle all over again with another drug. As an engineer with a background in biology, he thought there must be a better way.
Later Atray did his PhD in medical engineering at MIT, and did extensive research at the Broad Institute. He worked side by side with the inventors of CRISPR, and invented Perturb-Seq, a technique that combined single cell sequencing with CRISPR to understand how gene editing affects cell biology. Perturb-Seq is currently widely used to assist with drug development, and Atray decided to start Coral to leverage the same principles behind that technology to solve precision medicine for people like his family member.
Atray is the CEO. He has a PhD from MIT and BS from Princeton University. Prior to founding Coral, he has done research at the Broad Institute and invented Perturb-Seq. His unique background at the intersection of next-generation gene sequencing, machine learning and mechanical engineering plays a key role in building Coral's innovative platform.
Kasey and Sarah are Assay Development Scientists. Kasey has a PhD in Neuroanatomy, and was doing postdoc research at Stanford University on how DNA sequence variation associates with abnormal function of the nervous system. Sarah has a PhD in Molecular Biology from University of Strathclyde, where her research was focused on developing novel drug delivery systems for antibiotics and anti-cancer drugs.
Stevie is the Head of Strategic Partnerships. She is an experienced leader in business development in the healthcare industry. She has an MBA from Georgetown University and JD from Ohio Northern University. Before joining Coral, she first worked as an attorney and later as Senior Director at The Johns Hopkins University.
Pedro is the Lab Director. He has an MD from Harvard Medical School, and has extensive experience directing CLIA labs. Jose is the Clinical Laboratory Scientist. He studied organic chemistry at UC Davis and has managed many clinical labs. Rica is the Clinical Laboratory Scientist.
Open Roles - Senior Machine Learning Engineer
Coral is looking for a Senior Machine Learning Engineer to join their team. Here is the job description.
This role will report directly to CEO Atray. Main job responsibilities are to draw insights from the vast amount of RNA sequencing and drug response data Coral is generating.
Ideal candidate has PhD or MS in math, machine learning or bioinformatics with 3+ years industry experience. Strong preference towards candidates with a combination of experience in 1) deep learning/ML (PyTorch, Keras or TensorFlow), 2) cloud computing & big data processing and 3) a background in biology, especially human genetics and RNA sequencing. Candidate must be self-directed, a good communicator and thrives in a fast-paced startup environment.
Step 1 - Phone Screen: 30 minutes call with the hiring manager.
Step 2 - Technical Screening: 1 hour technical interview with the hiring manager over video call or onsite. For the Senior Machine Learning Engineer role, the technical interview includes a hands-on project with Coral's real genetic dataset that's been anonymized, and two conceptual problems about big data processing.
Step 3 - Onsite Interview: Lasting ~ 3 hours. Candidate will meet the whole team and present a project that they have worked on.
Company Culture Q&A
Q: What is the company's mission and what are your most important cultural values?
A: Coral's mission is to harness the diversity of human biology to improve therapies for all patients. Our most important cultural value is diversity.
Q: What is your company motto?
A: Our motto is "We'll figure it out". Sarah who's our first employee said that. A lot of things could go wrong at a startup, but we'll figure it out along the way.
Q: What are typical work hours at Coral?
A: Generally people work between 9am to 5pm, but it's not enforced.
Q: What is your remote work policy?
A: It depends on the role. Assay development scientists generally work onsite because they need to use the lab. For the Senior Machine Learning Engineer role, it's okay to work remotely as long as you join all our group meetings either in person or by calling in.
Q: What is your vacation policy?
A: Our paid time off is 120 hours throughout the year. In addition, we have 11 paid holidays.
Q: How many meetings do you have?
A: We have a Monday planning meeting every week, where people present projects and updates, and we plan out for the week. Every other Wednesday we have a brainstorming meeting where someone presents a paper and we discuss it. On Fridays we have casual team lunch.
Q: What about diversity?
A: Diversity is at the core of what we are doing, and it's our most important cultural value. Our team is currently majority women, and have 3 people from underrepresented ethnic backgrounds.
Q: What is your pet policy?
A: We love dogs! Atray brings in his dog Ari one or two times a week.
Q: What is your parental leave policy?
A: Generally we are very supportive and offer 16 weeks parental leave. However for the Senior Machine Learning Engineer role, we need someone who can work full-time for at least the first three months.
Q: Why are you excited to go to work everyday?
Atray: I'm excited to go to work everyday because it's an incredible learning opportunity. When building a startup, it is on you to learn everything needed quickly and figure out a solution among infinite possibilities. It is very motivating and very stressful at the same time. For me personally, hard & stressful things are very exciting.
Sarah: My favorite part of working here is the team. We have a very close-knit team, and we work really well together and are really good at problem solving. We often brainstorm together to find solutions and move things along very quickly.
Stevie: I love the culture here. We are very honest with each other and have an environment where people are comfortable sharing problems they're facing, and there's no negative connotation associated with that. I also think what we're working towards is really cool, and everyone on the team is very aligned around that goal.
Kasey: I'm excited to go to work because we all have the same goal, and we all want to see patients succeed. We also appreciate each other and feel that our voices are heard here.
All set! We'll be in touch if there's a fit.
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