Overview

We are seeking Senior AI/ML Engineers with 3 to 6 years of experience in implementing, deploying, and scaling AI/ML solutions.

Responsibilities

• Architect scalable Generative AI and Machine Learning applications using AWS Cloud and other cutting-edge technologies.
• Extensive experience with LLMs and various prompt engineering techniques.
• Fine-tune and build custom LLMs.
• Deep understanding of LLM architecture and internal mechanisms.

Qualifications

• Build RAG (Retrieval-Augmented Generation) pipelines and integrate them with traditional applications.
• Solve complex data science problems and uncover insights using advanced EDA techniques.
• Implement automated pipelines for data cleaning, preprocessing, and model re-training.
• Hands-on experience with model experiment tracking and validation techniques.
• Deploy, track, and monitor models using AWS SageMaker.
• Strong knowledge of fundamental machine learning concepts, including supervised and unsupervised learning, deep learning, CNNs, and RNNs.
• Proficiency in working with databases for efficient data storage and retrieval.
• Work on complex computer vision problems, including image classification, object detection, segmentation, and image captioning.
• 2-3 years of experience in implementing, deploying, and scaling Generative AI solutions.
• 3-7 years of experience in NLP, Data Science, Machine Learning, and Computer Vision.
• Proficiency in Python and ML frameworks such as Langchain, Langfuse, LLAMA Index, Langgraph, Crew AI, and LLM output evaluations.
• Expertise in forecasting, time series analysis, and predictive analytics.
• Proficiency in SageMaker for model training, evaluation, and deployment.
• Hands-on experience with ML libraries such as Scikit-learn, XGBoost, LightGBM, and CatBoost.
• Familiarity with Docker, Uvicorn, FastAPI, and Flask for REST APIs.
• Proficiency in SQL and NoSQL databases, including PostgreSQL and AWS DynamoDB.