Job Description

We are seeking a motivated

Biopharma Software Engineer

to build and maintain the computational infrastructure powering Lantern's AI-enabled oncology drug discovery programs. You will work closely with computational scientists and research teams to create scalable, robust systems that accelerate therapeutic development.

The ideal candidate will combine software engineering skills with interest in drug discovery, building cloud-native platforms which enable cutting-edge AI/ML research in precision oncology.

RESPONSIBILITIES:

Design, build, and maintain in silico molecule pipelines and infrastructure supporting AI/ML drug discovery projects Develop scalable data processing workflows for integrating public and proprietary preclinical and clinical datasets Implement cloud-based computing solutions for large-scale genomic and chemical data analysis Create and maintain APIs and tools enabling scientists to access computational resources and datasets efficiently Build data infrastructure for storing, versioning, and querying diverse biomedical databases including genomic, pathway, and drug response resources Collaborate with AI drug development scientists to understand computational requirements and optimize infrastructure Implement MLOps best practices for model deployment, monitoring, and versioning Ensure data security, compliance, and reproducibility across computational workflows Document systems architecture, pipelines, and infrastructure for team knowledge sharing Support computational scientists in troubleshooting technical issues and optimizing analyses

REQUIRED QUALIFICATIONS:

Bachelor's or Master's degree in Computer Science, Bioinformatics, Bioengineering, Computational Biology, or related field 3+ years of experience in software engineering, preferably in biotech, pharma, or healthcare settings Strong programming proficiency in Python and familiarity with scientific computing libraries (NumPy, Pandas, scikit-learn) Foundational understanding of LLMs and agential chat applications with experience working with OSS models and hosted APIs (OpenAI, Anthropic, etc.) Experience with cloud computing platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes) Knowledge of workflow management systems (Nextflow, Snakemake, Airflow, or similar) Familiarity with version control systems (Git) and CI/CD practices Understanding of databases (SQL and NoSQL) and data warehousing concepts Strong problem-solving skills and ability to work collaboratively with scientists Excellent communication skills for technical and non-technical audiences

PREFERRED QUALIFICATIONS:

Experience with biological data types (genomics, proteomics, chemical structures) Knowledge of ML frameworks (TensorFlow, PyTorch) and MLOps tools Understanding of serverless engineering and methods of implementation and deployment (Lambdas, AWS Sagemaker) DevOps experience with the ability to automate deployment processes and service monitoring Familiarity with drug discovery concepts or computational chemistry Experience working in remote/distributed team environments Understanding of data privacy and compliance requirements (HIPAA, GDPR)
Job Type: Full-time

Work Location: In person