(Senior) Machine Learning Engineer, Biomolecule Design

Company Summary

Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science.

Our Life Sciences effort is leveraging AI and high-throughput automation for valuable therapeutic discovery and development across biological modalities.

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

The Role

Lila Sciences is seeking a dedicated and skilled (Senior) Machine Learning Engineer, Biomolecule Design to join our team. Leveling is flexible based on experience. This role will focus on MLOps for training in large scale ML models of Protein, RNA and DNA. You will be part of a dynamic, cross-functional team responsible for developing and deploying machine learning models for sequence design. Working closely with biologists, bioinformaticians, software developers, and automation engineers, you will contribute to the development of ML models for a range of therapeutic applications.

The ideal candidate has a strong background in machine learning, as well as either experience in biotech industry or a record of scientific achievement, with a focus on MLOps, model training, and deployment.

Responsibilities include:

• Developing, training, and deploying machine learning models for Protein/RNA/DNA sequence design.
• Implementing MLOps practices to streamline the model development and deployment process.
• Collaborating with cross-functional teams to integrate ML models into the data pipelines for our labs.
• Gathering and pre-processing public datasets with bioinformatics tools to pre-train ML models.
• Implementing rigorous testing, documentation, and model benchmarking.

Qualifications:

• Master's degree in computer science, computational biology, physics, or other quantitative disciplines
• Experience with MLOps practices and tools including version control, automated testing, and CI/CD
• Experience in at least one ML framework (PyTorch/TensorFlow/Jax) and robust experience in the Python data science ecosystem.
• Experience with large language models (e.g. autoregressive LLMs) for biological sequences is a plus.
• Familiarity with bioinformatics tools and databases for pre-processing and analyzing biological sequence data.

Working at Lila, you would have access to advanced technology in the areas of:

• AI experimental design and simulation
• Automated liquid handling and instrumentation
• Generative molecular design

More About Flagship Pioneering

Flagship Pioneering is a platform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Flagship Pio