We are seeking a Senior Python Developer (Data Science) with a Software Engineer First mindset to join our core engineering team.

In this role, you won't just train ML models in notebooks—you will architect, build, and deploy high-performance FastAPI microservices, asynchronous data pipelines, and scalable NLP/LLM solutions into production cloud environments (AWS).

If you love writing clean, asynchronous Python code, optimizing REST APIs, and integrating cutting-edge NLP/GenAI tools into robust backend architectures, we want to hear from you!

Key Responsibilities

Backend Microservices: Design, build, and maintain production-ready REST APIs and asynchronous microservices using FastAPI (with async/await, Pydantic, and SQLAlchemy).
Data Engineering & ETL: Build scalable, high-throughput data processing pipelines handling structured and semi-structured data (JSON, Parquet, CSV, SQL) using Pandas and PySpark.
NLP & Model Integration: Integrate advanced NLP models, Transformers, LLMs, and RAG architectures (SpaCy, LangChain, Transformers, Rasa) directly into backend services.
MLOps & Deployment: Containerize applications using Docker and deploy ML endpoints via AWS SageMaker, AWS Lambda, and container registries (ECR).
Code Quality & Testing: Write clean, modular, object-oriented Python (OOP) with comprehensive unit/integration test suites using pytest (>85% coverage) and CI/CD pipelines.

Mandatory Qualifications (Must-Haves)

6+ years of professional software development experience in Python.
Proven track record building and deploying production FastAPI microservices and RESTful APIs.
Deep experience in data manipulation and ETL using Pandas, SQL, and Parquet/JSON formats.
Hands-on experience integrating NLP / Machine Learning frameworks (e.g., SpaCy, Transformers, LangChain, RAG, Rasa) into backend applications.
Production experience with AWS SageMaker (model hosting/endpoints) and Docker containerization.
Strong grasp of asynchronous programming (asyncio, Celery/Redis), design patterns, and testing with pytest.

Nice-to-Haves

AWS Certifications (Solutions Architect or Machine Learning Specialty).
Experience with Vector Databases (Qdrant, Pinecone, FAISS) or Multi-Agent frameworks (LangGraph, CrewAI).
Experience with message brokers like Apache Kafka or RabbitMQ.

Senior Python Developer (Data Science & NLP)