Here’s what makes you an Ideal Candidate for this position
Position
Sr. NLP Engineer
City
Ahmedabad
Experience
2-3 Years
Work Shift
Day Shift
About the Role
We are looking for an NLP Engineer with 2–3 years of hands-on experience in building AI applications, NLP pipelines, and LLM-based solutions. The ideal candidate should be comfortable working with RAG, transformer models, vector databases, and basic AI service integrations. The role involves working closely with senior engineers and product teams to develop and optimize NLP features.
Key Responsibilities
AI & NLP Development
Contribute to the development of AI/NLP features, chatbots, and automation solutions.
Implement RAG-based workflows including data chunking, embeddings, and vector search.
Work with vector databases like FAISS, Pinecone, Milvus, etc.
Build and maintain chatbot/assistant applications using LangChain.
Develop LLM workflows or agents using LangGraph (good to have).
Work with transformer models (BERT, GPT, LLaMA, RoBERTa) for tasks like classification, summarization, Q&A.
Integrate AI modules into larger systems using REST APIs or microservices.
System Architecture & Operations
Assist in designing and implementing model pipelines and workflows.
Deploy NLP models into test or production environments.
Work with containerization (Docker) and understand basics of Kubernetes (added advantage).
Use monitoring tools (Prometheus, Grafana, ELK, etc.) to track model performance.
Support model updates, retraining, and version control using Git and CI/CD workflows.
Cross-Functional Collaboration
Collaborate with Product Managers to define AI use cases and features.
Work with senior ML/NLP engineers to execute project milestones.
Participate in sprint planning, task estimation, and technical discussions.
Required Skills
Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or related field.
2–3 years of hands-on experience in NLP, ML, or LLM development.
Proficiency in Python and frameworks like LangChain or HuggingFace.
Experience with transformer models and understanding of embeddings.
Exposure to RAG pipelines and vector databases.
Good understanding of microservices, REST APIs, and containerized deployments.
Experience using Kafka, RabbitMQ, or AWS SQS (at least one).
Familiarity with ITSM or CRM platform integrations is a plus (ServiceNow, Jira, Salesforce).
Strong problem-solving, debugging, and documentation skills.
Good to Have
Experience with LangGraph or agent workflows.
Knowledge of MLOps concepts (model monitoring, versioning).
Hands-on with cloud environments (AWS/Azure/GCP).
Experience working in agile teams.
What We Offer
Opportunity to work on modern LLM, NLP & automation projects.
Mentorship from senior AI engineers and architects.
Learning-focused environment with growth opportunities.
Competitive compensation & benefits.
