SentientGeeks is seeking a passionate and skilled AI/ML Backend Engineer to join our growing Artificial Intelligence team.

The ideal candidate should have a strong foundation in Deep Learning, NLP, Python, Machine Learning, and database management, with hands-on experience in building and integrating backend systems for AI-driven applications.

Must-Have (Mandatory Skills) :

- Deep Learning & NLP : Practical experience in building, fine-tuning, and deploying deep learning models for NLP tasks such as embeddings, classification, and retrieval (RAG) pipelines.

- Machine Learning : Solid understanding of ML workflows - data preprocessing, model training, evaluation, and deployment.

- Python Programming : Strong proficiency in Python for backend and ML model integration.

- Vector Databases : Hands-on experience with one or more - FAISS, Pinecone, Weaviate, or PyMilvus.

Databases :

- SQL : Strong in MySQL

- NoSQL : Strong in MongoDB

- Backend Development : Expertise in developing RESTful APIs / microservices using FastAPI, Flask, or Django.

- Data Handling : Ability to manage structured and unstructured data in ML pipelines.

- Version Control : Proficiency with Git / GitHub / GitLab for collaborative development.

- Model Deployment : Experience deploying AI/ML models into production environments and optimizing inference performance.

Good-to-Have (Preferred / Bonus Skills) :

- MLOps : Familiarity with tools like MLflow, Kubeflow, Airflow, or Seldon.

- Computer Vision : Understanding of image-based model development and deployment.

- RPA Integration : Knowledge of Blue Prism or UiPath integration with AI components.

- Generative AI & LLM Tools : Experience with LangChain, LangGraph, LangSmith, Langflow, and similar frameworks.

- Agentic AI Frameworks : Exposure to AutoGen (Microsoft) or CrewAI.

- Workflow Automation : Familiarity with n8n, Airflow, or other orchestration tools.

- Vector DB Optimization : Experience in tuning FAISS, Weaviate, or PyMilvus for scalability.

- Containerization : Working knowledge of Docker for packaging and deployment.

- Event Streaming : Basic understanding of Kafka or RabbitMQ.

- GenAI Integrations : Practical knowledge of OpenAI, Hugging Face, or custom LLMs.

- Business Intelligence (BI) : Exposure to BI dashboards or data visualization tools (e.
, Power BI, Tableau).

Key Responsibilities :

- Design and maintain scalable backend systems to support AI/ML workflows.

- Integrate and serve deep learning/NLP models in production environments.

- Manage and query vector databases for semantic and similarity-based retrieval.

- Build secure and optimized APIs for AI-driven applications.

- Collaborate with data scientists to transform prototypes into deployable solutions.

- Implement automation and monitoring for model lifecycle management.

- Contribute to AI architecture discussions involving GenAI and agentic workflows.

Educational Qualification :

- B.Tech / M.Tech / MCA / M.Sc in Computer Science, IT, or equivalent field.

Soft Skills :

- Strong analytical and problem-solving mindset.

- Excellent communication and teamwork abilities.

- Eagerness to learn and explore new AI, MLOps, and GenAI framework