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Full Stack ML Engineer - Python/TypeScript

HiringBlaze
3 - 6 Years
Multiple Locations

Posted on: 29/08/2026

Job Description

Job Title: SDE II - Full Stack ML Engineer (Python / TypeScript)

Location: Hyderabad / Bangalore (On-site / Hybrid)

Experience: 3 6 Years

Compensation: Competitive / As per industry standards

Employment Type: Full-Time

About the Role:

We are seeking an experienced Full Stack SDE II to bridge the gap between data science and user-facing applications. In this role, you will build scalable backends, design intuitive frontends, and integrate cutting-edge Machine Learning and AI models into production environments.

Key Responsibilities:

- Architect and develop robust backend systems and APIs using Python (FastAPI, Django, or Flask).

- Build responsive, dynamic user interfaces and scalable middleware using TypeScript (React.js, Next.js, or Node.js).

- Integrate Machine Learning models (e.g., predictive analytics, NLP, LLMs) into production applications, ensuring low latency and high throughput.

- Collaborate closely with Data Scientists to operationalize AI pipelines and optimize ML model inference.

- Design and manage database architectures across both SQL (PostgreSQL) and NoSQL (MongoDB, Vector databases).

- Deploy, scale, and monitor full-stack ML applications using cloud infrastructure (AWS/GCP), Docker, and CI/CD pipelines.

Must-Have Qualifications:

- 3 to 6 years of production-level software engineering experience.

- Strong proficiency in Python for backend development and API design.

- Deep hands-on experience with TypeScript and modern frontend frameworks (React/Next.js).

- Proven experience integrating Machine Learning models into live software applications (MLOps, model serving, or AI API integrations).

- Solid understanding of relational databases and system design principles.

- Familiarity with cloud platforms (AWS) and containerization (Docker).

Good-to-Have Skills:

- Hands-on experience with Vector Databases (Pinecone, Weaviate) or RAG architectures.

- Experience with ML serving frameworks like Triton, Ray Serve, or ONNX.

- Background in building AI agents or working directly with LLM workflows.

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