- Ship stuff that makes our scientists say "this is amazing, thank you so much"
- Collaborate with folks from our machine learning, automation, and biology groups
- Directly shape our roadmap for empowering scientists
- 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
- Design a new domain specific data exploration tool and onboard our wetlab scientists.
- Design and implement a data extraction and transformation pipeline for a new microscope.
- Integrate a new physical instrument into our robotic automation stack.
- Add a feature to our internal ML experimentation system to improve performance profiling of multi-GPU training jobs.
- Placing a high degree of trust in your ideas and execution
- Bringing you up to speed in the domain of drug development
- Strive to provide a low-stress work environment
- Making ourselves available for collaboration
- Caring about you as a whole person - not a resource
- Being a well funded startup with conservative runway
- Working towards a BS, MS, or Ph.D. in an engineering, mathematics or a life sciences discipline
- You're eager to ship work that makes a difference to scientists and ultimately patients
- Experience in one or more general-purpose programming languages. We primarily use Python
- Ability to write high-quality code as demonstrated by prior experience, Github account or personal webpage
- Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
- Experience with biological data (e.g. DNA sequences, RNAseq, proteomics, microscopy)
- Experience in Linux environment, database languages (e.g., SQL, No-SQL) and version control practices and tools such a Git or Mercurial.
- Familiarity with the SciPy/PyData ecosystem (numpy, pandas, scipy, dask etc.)
- Familiarity with web services and application frameworks (Django, Flask)
- Familiarity with cloud computing services (AWS or GCP)
- Familiarity with data pipelines, workflow engines, distributed computing technologies (Spark, Hadoop, etc)
- Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees on our base plans), as well as mental health and well-being support
- Excellent mental health and well-being support
- Access to free onsite baristas and cafe with daily lunch and breakfast
- Access to free onsite fitness center
- Commuter benefits
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Software Engineering Intern - San Francisco, United States - insitro
Description
The Opportunity
At insitro, we are trying to greatly increase the success rate of drug development by combining human biology, lab automation, and machine learning, at scale.
Central to insitro's thesis is our ability to integrate rich datasets across modalities. From live cell imaging to single-cell RNA sequencing to DNA encoded libraries, insitro generates a diverse and ever growing torrent of data. Our software teams develop the foundation of lab orchestration software and data pipelines that transform that torrent into the actionable datasets driving our target and drug discovery efforts.
We are looking for highly motivated interns looking to work at this intersection of software engineering and the life sciences for our Summer 2024 cohort. You will partner directly with an engineering mentor and lead a project from inception to prototype over the course of the summer (11 weeks).
What you'll do day to day:
Examples of projects you will be working on:
In return, we will support you by:
About you
Nice to Have
Compensation & Benefits at insitro
Our target starting salary for successful US-based applicants for this role is $55/hr - $65/hr. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.
In addition, insitro also provides our interns:
insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience, oncology and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit