Scaling and deploying machine learning models for RNA design

Inceptive; Berlin; Vor Ort; USD 135.000 - 240.000; Vollzeit

Zusammenfassung

Join a forward-thinking company where you will drive the development of groundbreaking biological software that could help billions. This role focuses on creating essential infrastructure for machine learning models tailored for RNA design, ensuring efficient GPU utilization and seamless integration with wet-lab processes. You will work in a collaborative environment, tackling complex problems at the intersection of biology and computation. If you're passionate about innovative solutions and eager to contribute to transformative projects, this opportunity is perfect for you.

Leistungen

Bonus

Equity

Company Retreats

In-person Collaboration

Qualifikationen

• Experience in designing scalable machine learning systems.
• Proficiency in software design and automation tools.
• Ability to communicate technical concepts effectively.

Aufgaben

• Develop and scale foundation models for RNA, DNA, and proteins.
• Build infrastructure for large-scale training and deployment of models.
• Collaborate with diverse teams to solve complex biological problems.

Kenntnisse

Machine Learning Systems

Software Design

Infrastructure Scaling

Automation

Docker

Kubernetes

GCP

Postgres

BigQuery

Problem Solving

Jobbeschreibung

At Inceptive, you will drive development forward that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software.

More RNA sequences are coding for a single target protein than atoms in the universe. Each of these RNA sequences differs in ways that may radically affect how it performs when used in medicine. Faced with this search space, we believe that machine learning-based approaches are ideally placed to tackle the RNA design problem that we work on at Inceptive.

You will be responsible for creating essential infrastructure and tooling, encompassing model training, data transformations, inference, monitoring, profiling, and debugging. Your primary focus will be on enabling the swift development and deployment of generative models tailored for RNA design, ensuring our GPUs remain efficiently utilized for processing ever-expanding datasets. In addition, you will play a pivotal role in seamlessly closing the loop between models and biological assays in our wet-lab, implementing robust tooling and integration solutions.

Your Mission, should you choose to accept it

• Be part of a team that develops and scales a foundation model applied to RNA, DNA, and proteins on public and in-house data
• Design and build the infrastructure and tooling required to support large-scale training, rapid prototyping, and deployment of machine learning models and related systems
• Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise
• Collaborate with team members from diverse backgrounds to build innovative and scalable experiments to solve complex problems that span biology and computation

Qualifications

• Demonstrated experience designing and building scalable machine learning systems and tooling to enable a short path from rapid prototyping to reliable deployment
• Proficiency in software design, including the ability to identify appropriate abstractions and strike a balance between extensibility and development complexity
• Experience scaling infrastructure at hyper-growth startup or fast-growing team
• Extensive experience deploying and maintaining automation (e.g., CI, cron, …), dev environment (e.g., Docker, Kubernetes, GCP), and databases (e.g., Postgres, BigQuery, …) for a team of contributors
• Problem-solver who is equally excited by finding creative solutions to complex problems, as you are by executing on them
• Ability to communicate technical and scientific concepts to team members from a broad variety of backgrounds
• Ability to understand the big picture, while driving projects on the ground from beginning to end
• Deep knowledge in your traditional area of expertise with a strong eagerness to connect to and apply your skills in other areas
• Availability to accommodate working with team members across different time zones, with one or two meetings per week starting at 8am PT or finishing at 7pm CET
• Readiness to travel several times a year for company retreats and business events
• We value the benefits of in-person collaboration and prefer candidates who can easily and regularly connect at one of our office locations

Compensation

$135K – $240K + Bonus + Equity