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JobsInsitro

(Senior) Machine Learning Scientist, Oligonucleotides

Insitro

(Senior) Machine Learning Scientist, Oligonucleotides

Insitro

South San Francisco, CA

·

On-site

·

Full-time

·

1w ago

Compensation

$185,000 - $235,000

Benefits & Perks

401(k)

Healthcare

Mental Health

Unlimited PTO

Parental Leave

Learning Budget

Home Office Stipend

Commuter Benefits

Free Meals

401k

Healthcare

Mental Health

Unlimited Pto

Parental Leave

Learning

Home Office

Commuter

Meals

Required Skills

Python

Deep learning

Generative AI

RNA design

DNA design

Genomic sequence analysis

THE OPPORTUNITY:

Machine learning lies at the core of insitro's approach to rethinking drug development. We've built a TherML https://www.insitro.com/news/introducing-insitros-therml-rapidly-engineering-the-right-therapeutic-for-the-right-target/ Platform that uses AI to accelerate pan-modality therapeutic discovery from hit-finding through lead optimization. Our innovative approach enables us to rapidly design therapeutics against internally discovered novel targets, with models powered by some of the industry's largest and most comprehensive datasets.

We're looking for a Machine Learning Scientist who will be hands-on using our TherML platform to drive design on multiple oligonucleotide therapeutic programs while directly contributing to the development of our platform and ML models. This role offers an opportunity to translate cutting-edge ML into real-world impact on drug discovery. This role will report to the Senior Manager, Molecular Machine Learning and is a flexible hybrid (2 days per week in office) or remote (1 week per quarter on-site) role.

RESPONSIBILITIES:

Develop insitro’s TherML Platform:

  • Work with industry-leading knockdown and off-target datasets to train and finetune foundation nucleotide models

  • Develop oligonucleotide generative AI methods for on-target knockdown and off-target gene misregulation

  • Collaborate with our computational chemists to apply MD simulation and other in-silico modeling based approaches to optimize oligonucleotide design based on RNA-protein interactions

  • Collaborate with software engineering teams to build robust pipelines for active/iterative learning and automated DMTL cycles

  • Directly shape the roadmap for our TherML platform's evolution

Integrate AI to Drive Our Oligonucleotide Discovery Programs:

  • Collaborate cross-functionally with machine learning scientists and oligonucleotide scientists to design and prioritize novel compounds using model outputs

  • Apply predictive models and AI-enabled design methods to solve real molecular optimization challenges across multiple therapeutic programs

  • Track performance of our on-target knockdown and off-target models on discovery programs and translate those insights into model improvements

  • Communicate model capabilities, results, limitations, and recommendations clearly to diverse stakeholders in regular discovery team meetings

ABOUT YOU

  • PhD in computational biology, computer science, machine learning, cheminformatics, or related field

  • 0-3+ years of industry experience applying machine learning to oligonucleotide therapeutic discovery

  • Strong programming skills in Python and modern deep learning frameworks (Py Torch or Tensor Flow)

  • Demonstrated expertise in developing deep learning and/or generative AI methods for RNA and/or DNA

  • Understanding of RNA structure, siRNA/ASO mechanism of action, and mRNA design

  • Proficiency with genomic sequence analysis across species

  • Excellent communication skills with ability to translate technical concepts to diverse audiences

  • Familiarity with oligonucleotide therapeutics discovery process and design methods

COMPENSATION & BENEFITS AT INSITRO:

Our target starting salary for successful US-based applicants for this role is $185,000 - $235,000. 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.

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, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

  • 401(k) plan with employer matching for contributions

  • Excellent medical, dental, and vision coverage as well as mental health and well-being support

  • Open, flexible vacation policy

  • Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)

  • Quarterly budget for books and online courses for self-development

  • Support to attend professional conferences that are meaningful to your career growth and role's responsibilities

  • New hire stipend for home office setup

  • Monthly cell phone & internet stipend

  • Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid

  • Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com http://insitro.com, and if in doubt, contact us at info@insitro.com.

About insitro

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 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 www.insitro.com http://www.insitro.com.

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About Insitro

Insitro

Insitro

Series C

Biotechnology company.

201-500

Employees

South San Francisco

Headquarters

$2.4B

Valuation

Reviews

3.7

1 reviews

Work Life Balance

3.0

Compensation

4.0

Culture

2.5

Career

3.0

Management

2.0

25%

Recommend to a Friend

Pros

Well-funded company with resources to spend

Good perks for software and engineering teams

Company retreat opportunities

Cons

Lack of employee loyalty and engagement

Wasteful spending practices

Inconsistent experience across departments

Salary Ranges

28 data points

Mid/L4

Mid/L4 · Business Development

0 reports

$274,620

total / year

Base

-

Stock

-

Bonus

-

$233,427

$315,813

Interview Experience

53 interviews

Difficulty

3.3

/ 5

Duration

14-28 weeks

Offer Rate

34%

Experience

Positive 61%

Neutral 24%

Negative 15%

Interview Process

1

Phone Screen

2

Technical Interview

3

System Design

4

Behavioral

5

Team Fit

Common Questions

Tell me about a challenging project

System design question

Coding problem

Why this company