AI/ML Backend Engineer

SentientGeeks is Looking for an AI/ML Backend Engineer (2–3 Years Experience)

Location: Onsite

Experience: 2-3 years
Employment Type: Full-time

About the Role

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.g., 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 frameworks

Job Type: Full-time

Benefits:

• Health insurance
• Provident Fund

Ability to commute/relocate:

• Salt Lake City, West Bengal: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):

• How many years of experience you have in AI/ML Development ?
• Are you comfortable integrating AI outputs into BI dashboards (Power BI / Tableau)?
• Have you used Git / GitHub for version control and collaboration?
• What's the CTC you're getting ?
• What's the CTC you're expecting ?

Experience:

• Python: 3 years (Required)

Work Location: In person