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Remote, generalist full-stack ML role with mid-level experience requirement increases applicant competition significantly.
Core fullstack and ML production skills (React, Python, PyTorch, AWS) are broadly transferable across industries.
Explicit degree/experience gates plus mandatory ML, FastAPI, React, cloud and DevOps skills create strict shortlisting.
Design, develop, and own production ML-powered backend services, REST APIs, ETL pipelines, and dashboards used by clients and scientists.
Manage MLOps including deployment, model retraining workflows, versioning, CI/CD, observability, and drift monitoring for scalable ML systems.
Collaborate cross-functionally with data scientists and wet-lab scientists to translate scientific requirements into production-ready software solutions.
Master’s degree in Computer Science, Engineering, or related field with 2+ years experience OR Bachelor’s from Tier 1 Indian University with 5+ years experience.
Proven expertise building complex, responsive frontend web apps using React.js, Next.js, or Svelte.
Strong backend Python experience using FastAPI, Django, or similar frameworks.
Experience deploying and maintaining ML models and backend services on cloud platforms like AWS with DevOps/CI-CD skills.
Experienced software engineer comfortable bridging early-stage ML models to robust, maintainable production systems with modular architecture and rigorous testing.
Proficient across full-stack with strong domain knowledge of ML model serving, MLOps, and scalable cloud deployment.
Effective collaborator working well in agile, small teams interfacing between scientific research and engineering to deliver dependable AI-driven platforms.