GKM IT

Description : Role : Senior II Data Scientist, Generative AI & Advanced MLJob Summary :We are seeking a highly experienced and technically proficient Data Scientist - Senior II to drive innovation at the core of our intelligent systems. This role is a unique blend of cutting-edge Generative AI research, advanced Machine Learning (ML) model development, and technical leadership. The Senior II Data Scientist will be responsible for tackling high-impact business challenges by leading end-to-end ML projects from foundational research and model design through to production deployment. A critical component of this role is mentoring and technically guiding junior team members, shaping the future talent within the data science organization.Core Responsibilities :Advanced ML Research and Implementation :- Conduct in-depth machine learning research, continuously monitoring and evaluating state-of-the-art advancements, particularly in the Generative AI domain (LLMs, Diffusion Models, etc.).- Read, interpret, and rapidly implement complex methodologies described in academic and industry research papers, translating theoretical concepts into practical, working solutions.- Design, build, and rigorously evaluate sophisticated machine learning and deep learning models to address complex, high-value business problems across the organization.- Drive the entire end-to-end ML project lifecycle, from initial hypothesis formulation and data exploration to model deployment, monitoring, and iterative improvement in a production environment.Generative AI and LLM Development :- Apply deep familiarity with Transformer architectures and large-scale model optimization techniques to work directly with Large Language Models (LLMs).- Utilize and build upon orchestration frameworks like Langchain or LlamaIndex to design and engineer robust, production-ready LLM-based applications and autonomous agents.- Focus on pushing the boundaries of what is possible with data, specifically enabling new levels of insight, innovation, and decision-making capabilities within intelligent systems.Technical Leadership and Collaboration :- Actively mentor and guide junior data scientists and interns, providing technical direction, design feedback, and support in executing real-world projects.- Work collaboratively across engineering, product, and business teams to effectively turn data into decisions and models into high-value products.- Ensure the successful transition of theoretical models into production-ready code that meets enterprise standards for clarity, precision, performance, and security.Required Qualifications :Experience : 5 to 7 years of dedicated, progressive experience in Data Science or Machine Learning roles, with a proven track record of increasing responsibility.Statistical and Analytical Foundation : Strong foundation in Statistics and Probability, essential for model validity, experimental design, and interpretation of results.Programming and Libraries :- Advanced proficiency in Python for scientific computing, data manipulation, and building complex ML workflows.- Hands-on, expert-level experience with core data science and deep learning libraries, including Scikit-learn, Keras, TensorFlow, and PyTorch.Algorithm Expertise :- Expertise in core ML algorithms such as Linear/Logistic Regression, Decision Trees, Gradient Descent methods, Support Vector Machines (SVMs), and ensemble techniques.- Proven ability to select, adapt, and optimize algorithms for specific business goals.Generative AI/LLM Specialization :- Deep familiarity with Transformer architectures and practical experience in fine-tuning, prompt engineering, and working with pre-trained LLMs.- Practical experience with Langchain or LlamaIndex for building sophisticated, retrieval-augmented generation (RAG) or multi-step reasoning applications.MLOps Mindset : Proven ability to manage the operational aspects of ML models, including versioning, continuous training, and serving models in a low-latency production environment.Preferred Skills :- Experience with cloud-based ML platforms and services (AWS SageMaker, Google Vertex AI, or Azure ML).- Prior experience publishing technical research or contributing to open-source projects in the AI/ML space.- Working knowledge of Big Data technologies such as Spark/PySpark for handling and processing massive datasets.- Advanced specialization in a specific deep learning area, such as Computer Vision (CV), Natural Language Processing (NLP), or time-series forecasting.- Demonstrated ability to conduct A/B testing and design causal inference experiments. (ref:hirist.tech)