Software Engineer (Python)
Contract Position
We are seeking a highly motivated Scientific Software Engineer to join a leading biotech research team focused on accelerating small-molecule drug discovery through advanced machine learning and cheminformatics solutions.
In this role, you’ll collaborate with computational and experimental researchers to design, develop, and deploy Python-based workflows and user interfaces that streamline high-throughput experimentation and molecular design processes. This is a high-impact position at the intersection of software engineering, chemistry, and AI, supporting the development of next-generation therapeutics.
Key Responsibilities
- Implement Python-based workflows for cheminformatics and computational chemistry tasks.
- Collaborate with methods developers to enhance and maintain a large shared codebase using best practices (e.g., version control, testing, modular design).
- Deploy workflows on high-performance computing (HPC) and cloud platforms.
- Develop user-friendly, web-based tools and interfaces for scientists working in small molecule drug discovery.
- Benchmark and implement machine learning models for molecular property prediction and design optimization.
Required Qualifications
- BS, MS, or PhD in Computer Science, Engineering, or a related computational field.
- 1+ years of professional experience in scientific software development.
- Strong Python programming skills with experience building production-grade tools and workflows.
- Experience deploying and managing software on cloud or HPC infrastructure.
- Familiarity with collaborative development practices (e.g., Git, code review, automated testing).
- Strong communication and interpersonal skills; self-starter with a collaborative mindset.
- Foundational understanding of predictive and generative ML techniques in a scientific context.
Preferred Skills (Nice to Have)
- Familiarity with cheminformatics libraries such as RDKit or OpenEye Toolkits.
- 3+ years of relevant industry experience.
- Experience with large-scale chemical or biological datasets.
- Proficiency with modern ML frameworks (e.g., PyTorch).
- Experience deploying microservices with Kubernetes.
- Knowledge of workflow orchestration tools like Apache Airflow or Dagster.
- Public GitHub portfolio or demonstrable contributions to collaborative codebases.