Role Overview:
In this role, you will be contributing to advancing drug discovery technologies to benefit patients by shaping systems design decisions around our drug discovery platform, Proton. Design focus areas include data architecture, microservice design, and patterns for running compute-heavy Machine Learning jobs. Additionally, you will actively contribute to enhancing the codebase by participating in its development and improvement. You will serve as a role model, advocating for best practices in software development and engineering culture, while leading innovative projects that propel drug discovery forward. Successful candidates typically possess 5-10 years of experience and a bachelor's degree.
Key Responsibilities:
Technical Leadership and Execution: Lead the architectural design and contribute to the development of scalable web applications and microservices. Essential skills include proficiency in AWS, container orchestration frameworks, and Infrastructure as Code (IaC) best practices. You will collaborate with teams utilizing web development stacks comprising Python, modern frontend frameworks, and relational databases like PostgreSQL.
Mentorship and Collaboration: Take on a key role in mentoring engineers and fostering a culture of cross-team collaboration and continuous learning. Responsibilities include facilitating knowledge-sharing sessions, conducting code reviews, and providing one-on-one mentorship to nurture the technical growth of team members.
Engineering Culture and Best Practices: Drive the evolution of our engineering culture by advocating for and implementing best practices in Continuous Integration/Continuous Deployment (CI/CD), testing, monitoring, and code modularization. Ensure that engineering practices are scalable, efficient, and conducive to high-quality output.
Projects You May Lead:
Innovative Drug Discovery Projects: Collaborate with scientists and Machine Learning experts to address challenges such as expanding molecular search capabilities, designing automated AI-driven workflows for medicinal chemists, and developing tools for real-time data analysis in drug design processes.
Engineering Excellence Initiatives: Lead projects focused on enhancing our engineering framework, including improving CI/CD processes, setting new standards for code quality and testing, and implementing monitoring solutions for real-time insights into application performance.
Nice to Haves:
Experience consuming or deploying ML models and utilizing workflow orchestration frameworks like Kubeflow/Airflow.Familiarity with data pipelines.
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