Job description: Job Title: Full Stack Developer (Python/ JAVA) Location: Lucknow (onsite) Experience: 3-5 years Company: GC Cloud Info System PVT LTD Role Overview Technical Requirements — Python, Servers & Libraries - Deep Python backend expertise (3-5 years) with hands‑on experience building production services. - Application server models: - WSGI (synchronous): for traditional frameworks and blocking apps (e.g., Django synchronous views). Use when app is CPU/bounded or backward compatible with WSGI tooling. - ASGI (async-capable): for async IO, websockets, high-concurrency APIs (e.g., FastAPI, Django Channels). Use for real‑time, long‑polling, or high-throughput services. - Servers/runners: uvicorn (lightweight ASGI server, outstanding for development and production with workers), gunicorn (WSGI server; use with sync Django or with uvicorn workers for ASGI), hypercorn, daphne — know when to pair (e.g., gunicorn + uvicorn workers) and how to configure workers, timeouts, and graceful shutdown. - Common patterns: synchronous vs asynchronous view/handler design, event loop considerations, connection pooling, and CPU-bound task offloading (Celery/RQ/BackgroundTasks). - ORMs & DB access: - Relational ORMs: SQLAlchemy (Core & ORM), Django ORM, Peewee. - Async ORMs: Tortoise-ORM, SQLModel (with async SQLAlchemy), async SQLAlchemy usage patterns. - Migrations: Alembic, Django migrations. - Query optimization, indexing, transactions, connection pooling (psycopg2/asyncpg). - Vector DBs & embeddings: - Familiarity with vector search and integration: FAISS (library), Milvus, Weaviate, Pinecone, Qdrant. - Knowledge of embedding pipelines (sentence-transformers, OpenAI embeddings)



and building/maintaining indexes, similarity search, and hybrid search (vector + metadata filters). - ML / Computer Vision (initial/working experience expected): - Face recognition basics: OpenCV, dlib, face_recognition (based on dlib), InsightFace, familiarity with embeddings, face detection vs recognition, alignment, thresholds, and privacy/security considerations. - NLP, Topic Clustering & NER: - Core NLP/transformer libraries: Hugging Face Transformers, spaCy (including spaCy pipelines and training NER), NLTK, Gensim. - Topic modeling/clustering: classical (LDA via Gensim), embedding‑based approaches (BERTopic, clustering embeddings with HDBSCAN/KMeans), dimensionality reduction (UMAP/t-SNE). - Named Entity Recognition (NER): spaCy, Transformers-based NER, fine-tuning strategies, evaluation metrics. - Embeddings & pipelines: sentence-transformers, tokenization, batching, GPU acceleration for inference, handling long documents (chunking/aggregation). - Testing, observability & performance: - Unit/integration testing (pytest), API contract tests, load testing concepts. - Instrumentation: logging, Prometheus metrics, distributed tracing (OpenTelemetry), structured logs. - Security & deployment: - Auth patterns (OAuth2, JWT), rate limiting, CORS,



input validation (pydantic), secure storage of secrets. - Containerization and orchestration: Docker, Kubernetes basics; CI/CD pipelines for model/code deployments. Plus — Full Stack Universal Skills (desirable) - Frontend: React (preferred), Vue or Angular; strong JS/TypeScript, responsive UI, component-driven design. - Styling: CSS/Sass, Tailwind, Bootstrap, accessibility best practices. - API design: RESTful patterns, versioning, OpenAPI/Swagger; familiarity with GraphQL is a plus. - Testing: frontend testing (Jest/RTL), E2E testing (Cypress). - DevOps & infra: Git workflows, GitHub Actions/GitLab CI/Jenkins, IaC basics (Terraform/CloudFormation), CI/CD for ML models. - Databases & caching: PostgreSQL/MySQL, Redis, message queues (RabbitMQ/Kafka), backup/DR awareness. - Monitoring & SRE basics: Prometheus/Grafana, alerts, SLO/SLI awareness. - Soft skills: code reviews, design/architecture discussions, Agile/Scrum collaboration, clear technical documentation. - Optional but valuable: serverless (AWS Lambda), experience with SaaS/cloud-native product development, familiarity with data privacy/compliance (GDPR). Preferred Qualifications - Experience with microservices architecture and event-driven systems (Kafka, flask, RabbitMQ). - Knowledge of serverless technologies (AWS Lambda, Azure Functions). - Familiarity with infrastructure-as-code (Terraform, CloudFormation). - Experience with testing frameworks (pytest, frontend testing tools). - Prior work in cloud-native SaaS products. Work Location: In person Pay: ₹30,000.00 - ₹45,000.00 per month Work Location: In person

📌 Full Stack Developer (Python/java) (Lucknow)
🏢 GC Cloud Info System Pvt.Ltd.
📍 Lucknow