Introduction
As a Data Scientist at IBM, you will help transform our clients' data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it's investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.

Your Role and Responsibilities

• 12+ years of experience in Data Science with a background in machine learning, deep learning, and natural language processing.
• Robust background in traditional AI methodologies, encompassing both machine learning and deep learning frameworks.
• Familiarity with model serving platforms such as TGIS and vLLM.
• Hands-on experience in transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion) is desirable .Experience in testing AI algorithms and models is advantageous.
• Proficiency in Python, C++, Go, Java, and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality products is essential.
• Proficient in full-stack development, adept at frontend (HTML, CSS, JavaScript) and backend (Django, Flask, Spring Boot). Experience integrating AI tech into full-stack projects is a plus. Skilled in integrating, cleansing, and shaping data, with expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB.
• Proficient in developing optimal data pipeline architectures for AI applications, ensuring adherence to client's SLAs.
• Familiarity with Linux platform and experience in Linux app development is desirable.
• Experienced in DevOps, skilled in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes).
• Experience in Generative Ai would be a huge plus.
• AI compiler/runtime skills would be a huge plus.
• Open-source Contribution is a huge plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks is beneficial.
• Strong problem-solving and analytical skills, with experience in optimizing AI algorithms for performance and scalability.
• Familiar with Agile methodologies, adept at collaborative teamwork. Experience in Agile development of AI-based solutions is advantageous, ensuring efficient project delivery through iterative development processes.

• Lead the development and deployment of AI models in production environments, leveraging deep expertise in AI/ML and Data Science to ensure scalability, reliability, and efficiency.
• Direct the implementation and optimization of machine learning algorithms, neural networks, and statistical modeling techniques, personally driving solutions for complex problems.
• Personally oversee the development and deployment of large language models (LLMs) in production environments, demonstrating hands-on expertise in distributed systems, microservice architecture, and REST APIs.
• Collaborate closely with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, taking a hands-on approach to ensure seamless integration and efficiency.
• Proactively stay abreast of the latest advancements in AI/ML technologies and actively contribute to the development and improvement of AI frameworks and libraries, leading by example in fostering innovation.
• Effectively communicate technical concepts to non-technical stakeholders, showcasing excellent communication and interpersonal skills while leading discussions and decision-making processes.
• Uphold industry best practices and standards in AI engineering under your direct leadership, maintaining unwavering standards of code quality, performance, and security throughout the development lifecycle.

• 12+ years of extensive experience in Data Science and Generative AI.
• Deep background in machine learning, deep learning, and NLP.
• Hands-on expertise with transformer-based and diffuser-based models.
• Proficiency in traditional AI methodologies and frameworks.
• Familiarity with model serving platforms like TGIS and vLLM.
• Exceptional coding proficiency in Python, C++, and Java.
• Experience with ML libraries such as TensorFlow and PyTorch.
• Skilled in data integration, cleansing, and shaping.
• Proficient in developing data pipeline architectures.
• Experience with open-source AI frameworks and fostering a culture of learning.

• 12+ years leading AI/ML projects with a focus on scalability and precision.
• Skilled in implementing and optimizing machine learning algorithms and neural networks.
• Experienced in developing and deploying large language models, including distributed systems and microservices.
• Proficient in integrating MLOps with CI/CD tools for smooth AI/ML model deployment.
• Dedicated to advancing AI/ML knowledge and contributing to framework development.
• Effective at conveying technical concepts and fostering cross-team collaboration."