Full Stack Engineer

Company Overview

deep physics

Our culture is collaborative, science-driven, and innovation-focused, bringing together engineers, researchers, and domain experts to solve some of the most complex computational challenges in the industry.

Role Overview

Full-Stack Engineer

You will act as a bridge between sophisticated ML backends and intuitive user interfaces, empowering Geophysicists and Algorithm Developers to manage high-performance computational workloads efficiently while accelerating research and development.

Key Responsibilities

• Architect and develop scalable, production-grade full-stack applications using

  Django

  and

  Angular

  that serve as the central hub for scientific imaging workflows.
• Design and optimize systems that query, parameterize, and track complex machine learning workloads and high-compute jobs.
• Build tools that enable scientists to compare results, identify trends, and streamline quality control processes.
• Collaborate closely with internal users—including PhDs, Geophysicists, and Algorithm Developers—to translate complex scientific requirements into seamless, user-friendly UI/UX features.
• Proactively identify performance bottlenecks across dashboards, APIs, and database queries to ensure long-term reliability and scalability.
• Contribute across the full development lifecycle, from architecture and implementation to testing and continuous improvement.

Required Qualifications

• Bachelor’s or Master’s degree in

  Computer Science, Physics, Mathematics

  , or a related technical field.

• 3+ years

  of professional industry experience in full-stack software development.
• Strong proficiency in

  Python

  and either

  TypeScript or JavaScript

  .
• Demonstrated hands-on experience with both frontend and backend frameworks such as

  Django

  ,

  Angular

  , and

  RESTful APIs

  .
• Solid understanding of

  SQL

  and relational database technologies (e.g., PostgreSQL or MySQL).
• Experience working with

  machine learning workflows

  and agentic or ML-driven systems.
• Ability to work effectively in cross-disciplinary teams and communicate complex technical concepts clearly.

Preferred Skills

• Experience with cloud infrastructure and services such as

  AWS (EC2, S3, Lambda)

  .
• Familiarity with

  Docker

  and containerized deployments.
• Exposure to high-performance computing environments.
• Experience implementing or managing

  CI/CD pipelines

  .
• Knowledge of tools such as

  LangChain

  or

  RAG-based frameworks

  .

Work Schedule

• Monday to Friday (In Office)

Compensation & Benefits

• Yearly: 36 LPA - 40 LPA