Senior Generative AI/ML Engineer

Job Description : Responsibilities : - Lead the research, evaluation, and implementation of emerging AI/ML technologies, aligning with the company's strategic vision and product roadmap. - Design and develop complex POCs and MVPs to demonstrate the feasibility of advanced AI/ML solutions across diverse domains (infrastructure, storage, analytics, AI/ML, security). - Establish and enforce best practices for AI/ML development, deployment, and maintenance. - Optimize development processes and tool usage to ensure efficient and high-quality delivery. - Design and implement scalable and robust AI/ML architectures on cloud platforms, with a focus on Azure. - Lead the deployment and management of AI/ML models in production environments. - Conduct in-depth market research and competitive analysis to identify and evaluate relevant AI/ML technologies and solutions. - Align technology acquisition goals with the company's strategic objectives. - Predict and assess the long-term impact of emerging technologies on business applications and product roadmaps. - Drive innovation and explore new applications of AI/ML technologies. - Provide technical leadership and support for business development initiatives, including solutioning, estimations, RFI/RFP participation, and sales engineering. - Mentor and guide junior engineers, fostering a culture of technical excellence. Must-Have Skills : - 5 yrs of Experience. - Strong hands-on experience with Python-based web and backend frameworks (Django, Flask, FastAPI). - Generative AI (GenAI) : Extensive experience with LLMs (OpenAI, Gemini, Mistral, Falcon, etc. - Advanced knowledge of RAG and Multi-Modal RAG. - Proficiency with LangChain and Llama. - LLM Fine-tuning : Experience with PEFT, LoRA, QLoRA, and Adapters. - Expertise in NLP, sentiment analysis, topic modeling, Seq2Seq, attention models, tokenizers, TF-IDF, Word2Vec. - Tools : Advanced proficiency in Python, PyTorch, Keras, TensorFlow, OpenCV, SpaCy, Scikit-learn, Pandas, Git, SQL, Databricks, R. - Proficiency in SQL and NoSQL databases. Nice-to-Have Skills : - Machine Learning Techniques - Neural Networks - Deep Learning (CNN/RNN/LSTM) - Predictive modeling, EDA - Linear/Logistic Regression - Clustering, Nave Bayes - Ensemble, Gradient Boosting - XGBoost, SVM, Decision Trees - Random Forests, Knowledge Graphs. (ref:hirist.tech)

Location: pune, IN

Posted Date: 3/29/2025