Artificial Intelligence/Machine Learning Engineer
13 hours ago
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 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
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