Experience:

• 5-8 years in AI/ML development

Responsibilities:

• Develop, test, and optimize machine learning models across NLP, Computer Vision, and Predictive Analytics
• Build and implement transformer-based and traditional ML models
• Support data preprocessing, feature engineering, and model evaluation
• Implement APIs and integrate ML services into enterprise applications
• Implement LLM-based solutions including prompt engineering, embeddings, and basic fine-tuning
• Build Retrieval-Augmented Generation (RAG) pipelines
• Experiment with open-source and commercial LLMs such as GPT, LLaMA, Falcon
• Participate in model deployment workflows using Docker and CI/CD practices
• Monitor model performance and data drift
• Develop pipelines for data ingestion and model retraining
• Deploy and test ML solutions in cloud environments (AWS, Azure, GCP)
• Use cloud-native services such as S3, EC2, SageMaker
• Maintain structured and unstructured datasets
• Translate business requirements into ML tasks
• Communicate findings through documentation and dashboards
• Contribute to knowledge sharing and experimentation initiatives

Nice to have:

• Exposure to LangChain or LlamaIndex orchestration frameworks
• Understanding of vector databases like FAISS, Pinecone
• Basic knowledge of MLOps tools such as MLflow
• Experience with REST APIs or web app integration

More skills:

Retrieval-Augmented Generation (RAG), NumPy, SQL, Docker, APIs, AWS, Azure, GCP

Other:

• Opportunity to deepen technical expertise and gain exposure to real-world enterprise AI deployments
• Work alongside experienced leaders
• Build real-world expertise in emerging technologies including Generative AI
• Role not suitable for candidates seeking purely research-oriented roles or fully remote opportunities
• Ideal for hands-on contributors and team players comfortable in fast-paced environments