Job Description :
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 MySQLNoSQL : Strong in MongoDBBackend 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(ref : hirist.tech)