Senior / Staff Full Stack Software Engineer, Insitro

Clinical Data

$180-230k

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan

React
AWS
Docker
TypeScript
GCP
JavaScript
Python
Azure
Senior level
Remote in US
San Francisco Bay Area
Insitro

Machine learning drug discovery & development

Job no longer available

Insitro

Machine learning drug discovery & development

201-500 employees

B2BBiologyMachine Learning

Job no longer available

$180-230k

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan

React
AWS
Docker
TypeScript
GCP
JavaScript
Python
Azure
Senior level
Remote in US
San Francisco Bay Area

201-500 employees

B2BBiologyMachine Learning

Company mission

To become the first truly data-driven, integrated, drug discovery and development company.

Role

Who you are

  • You have 5+ years of experience as a professional software engineer with 3+ years of full stack web development experience
  • You're eager to ship work, wherever it is on the stack, that makes a difference to scientists and ultimately patients
  • You have a track record of turning ideas into maintainable and user-centric software products
  • You feel comfortable reasoning about the tradeoffs between quality and speed when building in a startup environment
  • You're familiar with the usual SWE things: AWS (or GCP/Azure), relational databases, writing design docs, version control, doing code reviews, perfecting our slackmoji game

Desirable

  • Experience navigating the regulatory landscape of drug development and a strong understanding of data privacy in clinical and genomic research
  • Experience with medium sized (100TB+) cellular or clinical datasets such as sequencing or histopathology
  • Experience with electronic medical records
  • Experience with data and machine learning pipelines
  • Experience with our stack: Python, Javascript/Typescript, React, SQLAlchemy, PostgreSQL, Docker, AWS

What the job involves

  • In this role, you will work primarily with heterogenous, multimodal clinical datasets, and build tools to help characterize cellular and patient state, predict the effect of clinical interventions, and design more successful clinical trials
  • To achieve this, you'll partner directly with machine learning scientists, biologists, engineers, and clinicians to design and build a cohesive platform for data ingestion, transformation, and exploration
  • Ship stuff that makes our scientists say "this is amazing, thank you so much!"
  • Collaborate cross-functionally with folks from our machine learning, automation, and biology groups
  • Directly shape our roadmap for empowering scientists
  • Shape our early-ish engineering culture with your ideas and experience
  • All the normal SWE stuff: write code, write and review design docs, talk to collaborators, and do code reviews
  • Ultimately you'll move the needle in a meaningful way for insitro and the field of medicine
  • Architecting components of our clinical data platform, spanning data ingestion, warehousing, and discovery
  • Building a data portal inspired by tools like HuBMAP and GDC, to make insitro's clinical data accessible to technical and nontechnical collaborators alike
  • Designing intuitive interfaces for visualizing and annotating radiology, digital pathology, and other high-content data and the insights that are derived from them
  • Embedding deeply with ML scientists, and helping them build multimodal models that map learned phenotypes to clinical outcomes

Our take

As pharmaceuticals become more specialised and complex, the traditional drug discovery process is becoming increasingly expensive and time consuming, taking up to 15 years from beginning to end. Insitro exists to reverse this trend by bringing a tech-first approach to the biopharma industry. By using machine learning to sort through vast amounts of medical data it is able to identify patterns in disease expression and identify targets for treatment.

This approach doesn't eliminate clinical trials but it augments the discovery process by highlighting productive areas of research. Perhaps the most difficut hurdle to overcome for Insitro is cultural: the huge pharmaceutical industry is used to relying on manual research and may have difficulty trusting machine learning guidance. However, this hasn't prevented their solution from being adopted by Gilead in their search for treatements for liver disease. It is also collaborating with Bristol Myers Squibb in ALS and dementia research. Should these partnerships prove successful Insitro stands to really shake up the pharmaceutical industry.

Freddie headshot

Freddie

Company Specialist at Welcome to the Jungle

Insights

Led by a woman
Top investors

28% employee growth in 12 months

Company

Funding (last 2 of 3 rounds)

Mar 2021

$400m

SERIES C

May 2020

$143m

SERIES B

Total funding: $643m

Company benefits

  • Excellent medical, dental, and vision coverage; insitro pays 100% of premiums for employees
  • Excellent mental health and well-being support
  • Open vacation policy
  • Access to free onsite baristas and cafe with daily lunch and breakfast
  • Access to free onsite fitness center
  • Commuter benefits
  • Paid parental leave
  • 401(k) matching
  • Flexible work schedule (on site and remote)
  • Monthly cell phone & internet stipend

Company HQ

The East Side, South San Francisco, CA

Leadership

Co-founder of Engageli and Coursera. Former COO and Calico Labs. Former Professor at Stanford University with a Post Doc in Computer Science from Berkley.

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