ML-Driven Software Engineer for Pharma Discovery

IMDiversity; Cambridge (MA); Hybrid; USD 79,000 - 106,000; Full time

Job summary

IMDiversity in Cambridge, MA seeks a Software Developer to advance machine learning-enabled chemical engineering applications and services. You will build and maintain command-line and web tools that deploy ML models for synthesis planning and property prediction, collaborating with faculty, researchers, and students.

You will containerize services with Docker and Kubernetes, develop scalable ELT pipelines, and help define APIs for ML deployment on chemical data.

Qualifications

• Bachelor's degree in computer science, chemical engineering, chemistry, or closely related field.
• Minimum of three years of experience with software/web development.
• Experience with Python applications in physical sciences.
• Familiarity with TensorFlow, PyTorch, or related ML code and version control workflows (Git, GitHub/GitLab).
• Experience with web-based, single-page apps using Vue or React.
• Experience in containerized and cloud-based infrastructure (Docker, AWS/EKS).

Responsibilities

• Professionalize software developed by team members.
• Maintain and develop a modern web application for long-running ML tasks and result visualization.
• Develop API standards and data structures for ML predictions in synthesis planning and property prediction.
• Define reproducible ELT pipelines for training ML models on chemical data.
• Prepare scripts to retrain and deploy ML models on user datasets.
• Package the application into containerized microservices for deployment using Docker and Kubernetes/EKS.
• Monitor application usage and set resource limits.

Skills

Python

ML frameworks

Web development

Git/GitHub

Docker

Kubernetes

Vue/React

Education

Bachelor's degree in CS, Chemical Eng, or Chemistry

Tools

Docker

Kubernetes/EKS

Git

Vue

React

TensorFlow/PyTorch

Job description

IMDiversity in Cambridge, MA seeks a Software Developer to advance machine learning-enabled chemical engineering applications and services. You will build and maintain command-line and web tools that deploy ML models for synthesis planning and property prediction, collaborating with faculty, researchers, and students.

You will containerize services with Docker and Kubernetes, develop scalable ELT pipelines, and help define APIs for ML deployment on chemical data.