Full-Time
Automation Engineer 3
Process Engineering
Posted on 9/13/2025
Insitro
201-500 employees
ML-driven predictive drug discovery and development
Compensation Overview
$120k - $130k/yr
San Bruno, CA, USA
In Person
Expected to be in the office five days per week.
 AI & Machine Learning (1) |
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- Bachelor's degree or higher in Robotics, Mechanical, Electrical, Chemical, Software or Bioengineering, or Physics, Chemistry or Biology
- 2+ years of relevant work experience
- Proficiency in Python, C# (or similar programming language)
- Experience automating scientific workflows (ex. Genomic Screening)
- Comfortable learning and supporting diverse automation equipment (e.g., liquid handlers, robotic arms, plate readers, plate washers etc)
- Develop and improve complex automation workflows on workstations and large-scale integrated systems
- Define and perform instrument qualification processes (IQ/OQ/PQ)
- Support workflow analysis, identify bottlenecks and highlight areas for improvement
- Support the lab teams in troubleshooting their workflows and methods. Provide root cause analysis
- Develop software to integrate automation software with LIMS
- Prepare and review design documents and participate in code reviews
- Develop device drivers to facilitate workcell integration
- Gain exposure to a wide range of technologies and approaches, broadening your technical toolkit
- Contribute directly to insitro's mission, while shaping both our culture and our scientific outcomes
- You are conscientious about your commitments to your team, maintaining best practices while prioritizing team goals
- You enjoy working together with scientific partners to iterate through solutions and support high quality data generation
Insitro uses machine learning and biology to speed up drug discovery and development by building predictive models from large-scale data to forecast which research paths will yield medicines, reducing costly failures in pharmaceutical R&D. It integrates data generation with ML to guide decisions on targets, molecules, and experiments, helping researchers focus on the most promising options. The company blends biology and ML in integrated workflows, supported by scientists and engineers who generate and interpret data for drug candidates. Its goal is to make pharmaceutical R&D more efficient and effective, shortening timelines and increasing the chances of delivering useful medicines, often via predictive insights or co-development partnerships with pharma companies.
Company Size
201-500
Company Stage
Series C
Total Funding
$643M
Headquarters
San Francisco, California
Founded
2018
Simplify's Take
What believers are saying
- Bristol Myers Squibb nominated ALS-2, ALS-3 targets, paying Insitro $10M milestone in March 2026.
- BAT-01 target achieved 15% weight loss in obese mice, preserving lean mass via AI GWAS.
- Joe Hand appointed Chief People Officer, leveraging Celgene experience for scaling operations.
What critics are saying
- Bristol Myers Squibb internalizes ALS-1, ALS-2, ALS-3 targets post-2025, terminating collaboration.
- Eli Lilly exits partnership like Gilead in 2024, cutting $150M revenue by mid-2027.
- FDA rejects BAT-01 IND in 2026 after mouse data fails human translation.
What makes Insitro unique
- Insitro's Virtual Human platform integrates AI with patient-derived iPSC motor neurons for ALS targets.
- TherML unifies small molecules, oligonucleotides, and antibodies via CombinAble.AI acquisition.
- POSH platform maps gene function using pooled CRISPR, imaging, and machine learning without biomarkers.
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Benefits
Excellent medical, dental, and vision coverage
Excellent mental health and well-being support
Open vacation policy
Access to free onsite baristas & cafe with daily lunch and breakfast
Access to free onsite fitness center
Commuter benefits
Paid parental leave
Competitive pay and 401(k) matching
Flexible work schedule (on site and remote)
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↓ -3%2 year growth
↑ 2%Developers expand collaboration to test 2 novel targets for ALS treatments. Insitro, Bristol Myers Squibb first struck deal in 2020 to use AI in lab research * Insitro and Bristol Myers Squibb are expanding a research collaboration deal, in place since 2020, to find new ALS treatments. * The two companies are using AI and patient-derived cells to identify biological targets for ALS therapies. * Two new targets aim to correct TDP-43 protein abnormalities, improving nerve cell health. Insitro and Bristol Myers Squibb have expanded their ongoing collaboration to develop new treatments for amyotrophic lateral sclerosis (ALS), adding two newly identified disease targets to their ongoing research effort. The two drug companies have been working together since 2020 to uncover biological changes driving ALS that may be reversed with therapies, using a combination of artificial intelligence (AI) and lab-grown human cells. The new targets, ALS-2 and ALS-3, build on previous work in the collaboration, which has already advanced a first target, dubbed ALS-1, into early development. The companies are already exploring different classes of therapies to act on the same disease target. "By expanding our collaboration with Bristol Myers Squibb, we are broadening our approach to tackling this devastating disease, with a set of compelling targets that address its fundamental mechanisms, with the goal of delivering disease-modifying therapies to the many patients who cannot wait," Daphne Koller, PhD, Insitro's founder and CEO, said in a company press release. A $10 million payment was tagged to target selection, according to Insitro. Recommended Reading ALS is caused by the progressive loss of motor neurons, the nerve cells that control voluntary movement. While the exact mechanisms leading to motor neuron degeneration and death are not fully understood, abnormal clumps of the TDP-43 protein are believed to play a role. Under normal conditions, TDP-43 is found in the nucleus, where genetic material is stored, and helps cells correctly process genetic instructions needed to make proteins. In about 97% of all ALS cases, however, TDP-43 forms clumps outside the nucleus and is no longer able to perform this function properly. AI helps create 'data-driven map' showing impact of ALS treatments. In the initial phase of the duo's collaboration, Insitro generated motor neurons from induced pluripotent stem cells (iPSCs), which are adult cells reprogrammed into a stem cell-like state. By using cells derived from patients or carrying mutations implicated in ALS, researchers were able to study the disease in a controlled setting and generate large datasets for analysis. Using its AI-based platform, the company analyzed these data alongside large clinical datasets to identify patterns and pinpoint biological pathways that are consistently disrupted in ALS and could be targeted with new therapies. "We are driven by a sense of urgency to translate our biological insights into meaningful clinical outcomes for the ALS community," said Koller. "Our platform allows us to build a data-driven map of the impact of ALS on motor neurons and identify novel drivers of neurodegeneration." So far, three new targets have been identified that may modulate the effects of TDP-43 abnormalities. These could have the potential to treat the vast majority of ALS patients, according to the company. Validation experiments using patient-derived motor neurons showed that modulating these targets increased neurite growth, a key indication of nerve cell health. This was accompanied by a reduction of the genetic abnormalities seen when TDP-43 is missing in the nucleus, and an increase in normal protein production. Under the terms of the agreement, Insitro has received the $10 million in milestone payments for the selection of the two new targets.
insitro has expanded its strategic collaboration with Bristol Myers Squibb to advance therapeutic programmes for amyotrophic lateral sclerosis (ALS). BMS has nominated two additional targets, ALS-2 and ALS-3, identified through insitro's AI-driven Virtual Human platform, joining the initial ALS-1 target nominated in December 2024. The companies will employ multiple therapeutic modalities to address the targets. insitro will advance an oligonucleotide programme for ALS-1 whilst simultaneously developing a small molecule programme for BMS. The strategy aims to maximise opportunities to impact patients quickly and effectively. insitro received a $10 million milestone payment for the selection of the two additional targets. The collaboration focuses on identifying key biological drivers to deliver disease-modifying interventions, specifically targeting processes that modulate TDP-43 mislocalization, a central disease mechanism in nearly 97% of ALS patients.
insitro and Bristol Myers Squibb collaboration expanded with nomination of new targets. Collaboration expands to include two additional therapeutic targets for the treatment of ALS discovered via insitro's AI-driven Virtual Human(TM) platform Joint effort focuses on identifying key biological drivers to deliver disease-modifying interventions for ALS patients SOUTH SAN FRANCISCO, Calif. - insitro, the AI therapeutics company built on causal biology, today announced the expansion of its strategic collaboration with Bristol Myers Squibb (NYSE: BMY) to advance a broadened portfolio of therapeutic programs for amyotrophic lateral sclerosis (ALS). The collaboration is focused on accelerating and delivering disease-modifying interventions designed to address the underlying biological drivers of ALS. BMS has nominated two additional targets, ALS-2 and ALS-3, which were identified through insitro's Virtual Human(TM) platform. These join the initial target, ALS-1, nominated by Bristol Myers Squibb in December 2024. The companies will leverage multiple therapeutic modalities to address the nominated targets. insitro will advance its own oligonucleotide program for ALS-1 while simultaneously progressing a small molecule program for BMS for ALS-1. This multimodality development strategy is designed to maximize the opportunities to impact patients as quickly and effectively as possible. insitro received a $10 million milestone payment in connection with the selection of the two additional targets. "We are driven by a sense of urgency to translate our biological insights into meaningful clinical outcomes for the ALS community," said Daphne Koller, Ph.D., founder and CEO of insitro. "Our platform allows us to build a data-driven map of the impact of ALS on motor neurons and identify novel drivers of neurodegeneration. By expanding our collaboration with Bristol Myers Squibb, we are broadening our approach to tackling this devastating disease, with a set of compelling targets that address its fundamental mechanisms, with the goal of delivering disease-modifying therapies to the many patients who cannot wait." Leveraging insitro's Virtual Human(TM) causal biology discovery platform, the company has identified a series of high-impact targets that play a central role in the biological mechanisms underlying ALS. By integrating massive-scale, human-derived cell data with machine learning, the Virtual Human(TM) allows for the mapping of disease drivers with unprecedented resolution, specifically focusing on processes that modulate the effects of TDP-43 mislocalization - a central disease mechanism in nearly 97% of ALS patients. In validation experiments using iPSC-derived motor neurons, modulation of these targets rescues neurite growth in cellular models of ALS - a significant milestone that reflects structural repair in human neurons. This is accompanied by reduction of the cryptic exons and restoration of the corresponding full-length transcript by a significant amount, reversing key markers of disease pathology that occur broadly in ALS patients. This also provides strong evidence supporting the potential of these targets to lead to disease-modifying therapies. About insitro insitro is the physical AI company unlocking causal human biology, founded and led by AI pioneer Daphne Koller. By generating the world's largest integrated multimodal corpus of human and cellular data, Insitro, Inc. has built the Virtual Human(TM)- a genetically anchored causal AI engine that reveals how disease begins, progresses, and can be resolved. Its platform enables Insitro, Inc. to precisely identify causal genetic drivers and deploy its TherML AI platform to design optimal medicines, advancing a broad pipeline of therapeutics for neuroscience and metabolic diseases. This industrialized architecture creates a self-learning loop: with every biology Insitro, Inc. onboard, its predictive models grow smarter, accelerating discovery across scales of biology. Backed by ~$800M in capital from world-class investors like a16z, ARCH, Blackrock, Casdin, CPP, Foresite, GV, Softbank, Temasek, Third Rock, T. Rowe Price - including ~$150M in revenue from collaborations with BMS, Lilly, and Gilead - insitro is rebuilding drug discovery from an unpredictable journey into an industrialized, repeatable process with scalable impact for patients and the world. Media Contact Eric McKeeby [email protected]
insitro, an AI therapeutics company, has appointed Joe Hand as Chief People Officer to lead its global talent strategy as it scales operations and advances drug discovery programmes toward clinical trials. Hand brings over two decades of life sciences leadership experience, including nearly a decade at Celgene, where he served as Chief Human Resources Officer. At Celgene, he led HR operations during major transactions, including the $74 billion Bristol Myers Squibb acquisition and the $9 billion Juno acquisition. He also served as Chief Administrative Officer at Phathom Pharmaceuticals, building its HR infrastructure from inception. Founded by AI pioneer Daphne Koller, insitro uses integrated AI and biology platforms to discover medicines for neuroscience and metabolic diseases. The company has raised approximately $800 million from investors including a16z, ARCH and Softbank.
insitro has completed the first AI-enabled genome-wide association study of brown adipose tissue (BAT), identifying genetic targets with anti-obesity effects. The company used machine learning to analyse Dixon MRI scans from 69,598 UK Biobank participants, creating a BAT phenotype that previously required specialised PET scans. The study identified a prioritised target, BAT-01, which produced 15% body-weight reduction in diet-induced obese mice whilst preserving lean mass through peripheral adipose beiging, distinct from centrally acting appetite suppressants. The phenotype showed seasonal variation consistent with BAT biology, with the strongest signal in late winter. The findings, presented at the Keystone Symposia on Obesity Therapeutics, demonstrate how AI enables population-scale genetic analysis of tissues historically challenging to study in large cohorts.