Staff Software Engineer
3 days ago
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 established 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 platform’s 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 …- 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.
- 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.
- 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.
- Bachelor’s 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.
- 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.
- 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.
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