<p>Job Description :</p><p><br/></p><p>We are seeking Senior AI/ML Engineers with 3 to 6 years of experience in implementing, deploying, and scaling AI/ML solutions.
This role involves working with generative AI, machine learning, deep learning, and data science to solve business challenges by designing, building, and maintaining scalable and efficient AI/ML applications.<br/><br/>Key Responsibilities : </p><p><br/></p><p>AI : <br/><br/>- Architect scalable Generative AI and Machine Learning applications using AWS Cloud and other cutting-edge technologies.<br/><br/>- Extensive experience with LLMs and various prompt engineering techniques.<br/><br/>- Fine-tune and build custom LLMs.<br/><br/>- Deep understanding of LLM architecture and internal mechanisms.<br/><br/>- Experience with Langchain, Langgraph, Langfuse, Crew AI, LLM output evaluations, and agentic workflows.<br/><br/>- Build RAG (Retrieval-Augmented Generation) pipelines and integrate them with traditional applications.<br/><br/>Data Science & Machine Learning : <br/><br/>- Solve complex data science problems and uncover insights using advanced EDA techniques.<br/><br/>- Implement automated pipelines for data cleaning, preprocessing, and model re-training.<br/><br/>- Hands-on experience with model experiment tracking and validation techniques.<br/><br/>- Deploy, track, and monitor models using AWS SageMaker.<br/><br/>- Strong knowledge of fundamental machine learning concepts, including supervised and unsupervised learning, deep learning, CNNs, and RNNs.<br/><br/>- Proficiency in working with databases for efficient data storage and retrieval.<br/><br/>- Experience with data warehouses and data lakes.<br/><br/>Computer Vision : <br/><br/>- Work on complex computer vision problems, including image classification, object detection, segmentation, and image captioning.<br/><br/>Skills & Qualifications : <br/><br/>- 2-3 years of experience in implementing, deploying, and scaling Generative AI solutions.<br/><br/>- 3-7 years of experience in NLP, Data Science, Machine Learning, and Computer Vision.<br/><br/>- Proficiency in Python and ML frameworks such as Langchain, Langfuse, LLAMA Index, Langgraph, Crew AI, and LLM output evaluations.<br/><br/>- Experience with AWS Bedrock, OpenAI GPT models (GPT-4, GPT-4o, GPT-4o-mini), and LLMs such as Claude, LLaMa, Gemini, and DeepSeek.<br/><br/>- Experience with vector databases like Pinecone, OpenSearch, FAISS, and Chroma, with a strong understanding of indexing mechanisms.<br/><br/>- Expertise in forecasting, time series analysis, and predictive analytics.<br/><br/>- Experience with classification, regression, clustering, and other ML models.<br/><br/>- Proficiency in SageMaker for model training, evaluation, and deployment.<br/><br/>- Hands-on experience with ML libraries such as Scikit-learn, XGBoost, LightGBM, and CatBoost.<br/><br/>- Experience with deep learning frameworks such as PyTorch and TensorFlow.<br/><br/>- Familiarity with Docker, Uvicorn, FastAPI, and Flask for REST APIs.<br/><br/>- Proficiency in SQL and NoSQL databases, including PostgreSQL and AWS DynamoDB.<br/><br/>- Experience with caching technologies such as Redis and Memcached.</p> (ref:hirist.tech)