AI Scientist

At DNOVO Labs, we’re revolutionizing drug delivery through advanced artificial intelligence. We apply cutting-edge machine learning techniques to accelerate the discovery and optimization of innovative delivery systems. Our AI-driven approach enables rapid exploration of vast chemical spaces, allowing us to design and iterate on molecular structures that can transform how drugs and vaccines are transported in the body. This work is tightly coupled with our state-of-the-art wet lab, where we rapidly synthesize and test the most promising candidates, creating a seamless loop between in silico predictions and experimental validation.

You'll develop novel algorithms and machine learning architectures to accelerate the drug discovery and delivery process, working hand-in-hand with our lab scientists to translate complex biological data into actionable insights. Your day-to-day will involve not only model development but also regular interactions with our wet lab teams, ensuring that your algorithms address real-world biological challenges. As part of a multidisciplinary team, you'll work alongside software engineers to deploy robust systems, liaise with business leads to align technical solutions with strategic goals, and partner with scientists to monitor and iterate on deployed models. Your role is pivotal in bridging the gap between computational innovation and practical laboratory applications and your position will allow you to see the direct impact of your work on the end to end process.

Key Responsibilities:

• Develop foundational generative models for designing novel chemical structures and compounds used in drug/vaccine delivery systems.
• Design, build, maintain and scale production machine learning models.
• Help scale and build the computational / machine learning team.
• Collaborate extensively with the wet lab and platform teams to improve and iterate on therapeutic applications.
• Establish best practices for model development, validation, and deployment within the team.
• Present findings and progress to both technical and non-technical stakeholders, including leadership.

You may thrive in this role if you have:

• A master's or PhD in computer science, machine learning, or related field.
• 5+ years experience building, deploying production machine learning models.
• Advanced proficiency with Python.
• Proficiency with machine learning frameworks like PyTorch, Tensorflow, or JAX.
• Strong mathematical foundations and understanding of the principles of machine learning, including network architectures, evaluation metrics, and optimization techniques.
• Strong foundations in software engineering and algorithms design.
• Ability to work in a fast paced environment where things are rapidly changing and objectives are loosely defined.
• Enjoy working on end-to-end problems and are interested in defining and implementing complex technical solutions.
• Interest in computational chemistry, biology, and healthcare.

Nice to haves:

• Experience building machine learning models for biological or chemical applications.
• Are familiar with state of the art generative models (e.g. LLMs, diffusion, VAEs, GANs, EBMs).
• Have a publication track record at conferences such as NeurIPS, ICML, ICLR, etc.
• Familiarity with lab processes and wet lab experimental pipelines.

Location

This role will be remote initially but may transition to a hybrid role.