Machine Learning Engineer

 

As a Machine Learning Engineer at Redesign Science, you will play a crucial role in architecting and building systems and pipelines to scale our machine learning (ML) and molecular dynamics (MD) platform. We are building the world’s best structure-based drug discovery platform leveraging cutting-edge molecular dynamics and machine learning, and you will play a critical role in helping scale the platform. This is an exciting opportunity to help us shape, implement and improve our ML, MD and data systems and architectures, as well as helping to shape the direction and future growth of our ML engineering team.

 

 

Redesign Science uses machine learning and molecular dynamics to accelerate drug discovery and unlock new targeted therapies. We combine enhanced sampling and ML-accelerated MD to model drug-protein motion with deep nets trained on synthetic data to score billions of compounds and generative models to generate optimized molecules. Our computational platform has allowed us to rapidly build a pipeline of small molecules which modulate protein-protein interactions to drug formerly undruggable targets.

 

Our team is an interdisciplinary mix of experts in machine learning, molecular dynamics, chemistry, biology, and software engineering. As we expand our team, we are focused both on driving cutting-edge research to further improve our platform and on scaling our platform and discovery efforts to enable us to execute on more drug programs, faster.

Responsibilities

• Design, implement and integrate systems and pipelines for developing, training, and testing ML and MD methods at scale
• Productionize and scale machine learning models, physical simulations, and combined workflows
• Integrate ML systems with data pipelines for seamless data flow and processing across our entire infrastructure
• Work with the team to identify areas for improvement and optimization within our existing ML and MD systems
• Help shape the future growth and direction of our methodology and engineering teams

Essential Requirements

• Excellent software engineering skills and familiarity with development best practices
• Excellent knowledge of the Python programming language and relevant libraries
• Experience with modern ML systems, models and frameworks
• Experience with data infrastructure and engineering at scale
• Experience with workflow orchestration, MLOps, and machine learning pipelines
• Experience with continuous integration and continuous deployment tools and practices
• Excellent communication skills, able to present complex concepts effectively

Nice to have

• Experience leading the implementation of large-scale data-driven systems
• Strong experience working with PyTorch and with deep learning at scale
• Experience with SQL and working with / developing databases
• Experience with machine learning in a production setting
• An interest in biotechnology or drug discovery

Personal attributes

• Proactive and self-directed, with a strong sense of ownership over projects as well as over business outcomes outside the JD
• Strong problem-solving skills and first-principles reasoning abilities
• Adaptable and able to learn new technologies and concepts quickly
• Passionate about fostering technical and engineering excellence within the team and across our stack

For US-based applicants the standard base salary range for this position is $120,000 - $210,000 annually, plus competitive equity and benefits including medical, dental and vision insurance. This standard salary range encompasses several career levels, and compensation offered will depend on qualifications, skills and experience.