Staff Software Engineer

Cloud Biotech Platform

Posted on 9/6/2023

11-50 employees

Website

Protein therapeutics biotech company

Company Overview

1910 Genetics is on a mission to use AI/ML to develop drugs against historically difficult disease targets. 1910 Genetics puts computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, genetics, data science, and software engineering to develop drugs for previously undruggable targets.

Locations

Cambridge, MA, USA

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

AWS

Data Analysis

Data Structures & Algorithms

Django

Docker

Flask

Google Cloud Platform

Java

Microsoft Azure

Scala

Kubernetes

Python

CategoriesNew

Software Engineering

Requirements

Collaborate closely with cross-functional teams, including data scientists, AI/ML Engineers, Bioinformaticians, and domain experts, to build scalable data pipelines, integrate machine learning models, and ensure seamless platform functionality
Play a pivotal role in designing, developing, and maintaining a state-of-the-art cloud-based platform that empowers our scientists and researchers to make groundbreaking advancements in drug discovery
Bachelor' or master's degree in computer science, Software Engineering, or a related field
Proven experience (5+ years) in designing and building large-scale cloud platforms, preferably in a life sciences or pharmaceutical context
Strong expertise in cloud technologies such as AWS, Azure, or GCP, and hands-on experience with services like EC2, S3, Lambda, Kubernetes, and others
Proficiency in programming languages such as Python, Java, or Scala, and experience with web frameworks (e.g., Django, Flask) for building APIs and user interfaces
Solid background in data engineering, ETL processes, and data modeling for complex scientific datasets
Previous involvement in machine learning and AI projects, with a deep understanding of deploying and managing ML models in production
Familiarity with containerization and orchestration tools (Docker, Kubernetes) for deploying and scaling applications
Excellent problem-solving skills, ability to work independently, and a collaborative mindset for effective teamwork
Strong communication skills to convey complex technical concepts to both technical and non-technical stakeholders

Responsibilities

Lead the architecture, design, development, and deployment of a robust and scalable cloud-based platform tailored for early drug discovery processes
Integrate machine learning and artificial intelligence algorithms into the platform to enable predictive analytics, data mining, and pattern recognition
Collaborate with multidisciplinary teams to understand domain-specific requirements and translate them into technical solutions
Build and maintain efficient data pipelines to handle large-scale data acquisition, storage, and processing
Ensure the security, reliability, and performance of the platform, adhering to best practices for cloud infrastructure
Mentor and provide technical guidance to junior engineers, fostering a culture of continuous learning and growth
Contribute to code reviews, documentation, and knowledge sharing within the engineering team
State-of-the-art AI and ML technologies, staying at the forefront of innovation in drug discovery
Gain deep insights into the drug development lifecycle, learning how AI and ML techniques are applied to accelerate and optimize various stages, from target identification to clinical trials
Translate high level strategy into a software platform that meets and exceeds customer needs
How to design and build scalable cloud platforms
Identify the 80/20 of a feature and use rapid iterations to meet customer's needs
Mentor and coach junior engineers in software design patterns, code reviews, and ensuring code quality and maintainability
Foster effective teamwork and communication within the team, teaching colleagues how to convey technical concepts to non-technical stakeholders

Company Overview

1910 Genetics is the only company that has built a synergistic, dual-purpose small and large molecule platform that integrates artificial intelligence (AI), computation, and biological automation to design drug-like molecules better, faster, and cheaper than traditional approaches.

Based in the Seaport District of Boston, 1910 Genetics is a Series A stage biotechnology startup that was founded in 2018 and is backed by prestigious investors, including M12-Microsoft’s Venture Fund, Sam Altman – the CEO of OpenAI (makers of ChatGPT), Playground Global, Y Combinator, New Ventures Funds (Scientia Ventures), and many others.

At 1910 Genetics, we first establish an understanding of the molecular basis of disease to the granularity at which the world understands sickle cell anemia. This understanding centers biology as our North Star and drives our integration of artificial intelligence (AI), computation, and biological automation to accelerate the design of small molecule and protein therapeutics.

Recent advances in computational technologies have placed historically “undruggable” targets within therapeutic reach. But at 1910 Genetics, we often say “Biology is King,” meaning that computational technologies are only impactful in drug discovery when driven by experimental biology. Our platforms’ scale and breadth empower us to be therapeutic area-agnostic with programs ranging from neuroscience and immunology to infectious disease and oncology, to name a few.

You are someone we can count on to…

·Collaborate closely with cross-functional teams, including data scientists, AI/ML Engineers, Bioinformaticians, and domain experts, to build scalable data pipelines, integrate machine learning models, and ensure seamless platform functionality.

·Play a pivotal role in designing, developing, and maintaining a state-of-the-art cloud-based platform that empowers our scientists and researchers to make groundbreaking advancements in drug discovery.

Your key responsibilities will include…

Lead the architecture, design, development, and deployment of a robust and scalable cloud-based platform tailored for early drug discovery processes.
Integrate machine learning and artificial intelligence algorithms into the platform to enable predictive analytics, data mining, and pattern recognition.
Collaborate with multidisciplinary teams to understand domain-specific requirements and translate them into technical solutions.
Build and maintain efficient data pipelines to handle large-scale data acquisition, storage, and processing.
Ensure the security, reliability, and performance of the platform, adhering to best practices for cloud infrastructure.
Mentor and provide technical guidance to junior engineers, fostering a culture of continuous learning and growth.
Contribute to code reviews, documentation, and knowledge sharing within the engineering team.

Ideally, you have…

Bachelor’ or master’s degree in computer science, Software Engineering, or a related field.
Proven experience (5+ years) in designing and building large-scale cloud platforms, preferably in a life sciences or pharmaceutical context.
Strong expertise in cloud technologies such as AWS, Azure, or GCP, and hands-on experience with services like EC2, S3, Lambda, Kubernetes, and others.
Proficiency in programming languages such as Python, Java, or Scala, and experience with web frameworks (e.g., Django, Flask) for building APIs and user interfaces.
Solid background in data engineering, ETL processes, and data modeling for complex scientific datasets.
Previous involvement in machine learning and AI projects, with a deep understanding of deploying and managing ML models in production.
Familiarity with containerization and orchestration tools (Docker, Kubernetes) for deploying and scaling applications.
Excellent problem-solving skills, ability to work independently, and a collaborative mindset for effective teamwork.
Strong communication skills to convey complex technical concepts to both technical and non-technical stakeholders.

You will learn…

State-of-the-art AI and ML technologies, staying at the forefront of innovation in drug discovery.
Gain deep insights into the drug development lifecycle, learning how AI and ML techniques are applied to accelerate and optimize various stages, from target identification to clinical trials.
Translate high level strategy into a software platform that meets and exceeds customer needs.

You will teach…

How to design and build scalable cloud platforms
Identify the 80/20 of a feature and use rapid iterations to meet customer’s needs.
Mentor and coach junior engineers in software design patterns, code reviews, and ensuring code quality and maintainability.
Foster effective teamwork and communication within the team, teaching colleagues how to convey technical concepts to non-technical stakeholders.

Compensation and Benefits

Competitive Compensation Package
Above market benefits
Generous vacation and parental leave
Super cool team building activities
Flexible work schedule (3 days onsite)
Great colleagues