IBM AI Architect 

India, Karnataka, Bengaluru 

190633413

• Demonstrated leadership with around 20 years of experience in the systems industry. Has around 7-10 years of experience exclusively in Data Science, specializing in machine learning, deep learning, and natural language processing. Proven ability to lead teams and take ownership of end-to-end activities.
• Ability to architect AI solutions and lead complex AI missions.
• Strong working experience in the big endian systems, network concepts, GPUs.
• Strong grounding in traditional AI methodologies, covering machine learning and deep learning frameworks, with the capacity to guide and mentor team members.
• Proficient in utilizing model serving platforms such as TGIS and vLLM, with a knack for overseeing project implementations from conception to delivery.
• Preferred expertise in transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion), coupled with hands-on involvement in testing AI algorithms and models.
• Preferred expertise in parallel programming, HPC
• Mastery of Python, C++, Go, Java, and relevant ML libraries (e.g., TensorFlow, PyTorch) for developing top-tier, production-grade products. Proven ability to lead technical teams in the implementation of complex solutions.
• Skillful in full-stack development, encompassing frontend (HTML, CSS, JavaScript) and backend (Django, Flask, Spring Boot), with demonstrated experience in integrating AI technology into full-stack projects. Proficient in data integration, cleansing, and shaping, with expertise in various databases including open-source options like MongoDB, CouchDB, CockroachDB.
• Capable of designing optimal data pipeline architectures for AI applications, ensuring adherence to client SLAs, while guiding team members in achieving project milestones.
• Familiarity with Linux platforms and experience in Linux app development, demonstrating leadership in guiding teams through the development lifecycle.
• Proficient in DevOps practices, including Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes), with a proven ability to lead teams in adopting efficient development workflows.
• Experience in Generative AI is highly advantageous, with the ability to provide leadership and direction in exploring innovative AI techniques.
• Proficiency in AI compiler/runtime skills, showcasing leadership in driving optimization efforts and performance enhancements.
• Highly valued for open-source contribution, exhibiting leadership by actively participating in and guiding team members through contributions to open-source AI projects and frameworks.
• Strong problem-solving and analytical skills, coupled with the proven ability to lead teams in optimizing AI algorithms for performance and scalability.

• What you will do (Roles & Responsibilities):
• 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.
  Demonstrate leadership in the use of container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, personally overseeing deployment strategies and optimizations.
• Adept in Agile methodologies, with a track record of leading collaborative teams in Agile development of AI-based solutions. Demonstrated ability to take ownership of projects, ensuring efficient project delivery through iterative development processes.

Required Technical and Professional Expertise

• Data Science and Generative AI Leadership:
• Over 12 years of extensive experience in Data Science and Generative AI, demonstrating solid coding skills, leadership capabilities, and end-to-end ownership.
• Deep background in machine learning, deep learning, and natural language processing, serving as a mentor and leader in these domains.
• Model Development Expertise:
• Hands-on expertise with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion), showcasing mastery in model development and optimization.
• Desirable experience in rigorously testing AI algorithms and models, ensuring robustness and reliability in real-world applications.
• Traditional AI Methodologies Mastery:
• Demonstrated proficiency in traditional AI methodologies, including mastery of machine learning and deep learning frameworks.
• Familiarity with model serving platforms such as TGIS and vLLM, with a track record of leading teams in effectively deploying models in production environments.
• Proficient in developing optimal data pipeline architectures for AI applications, taking ownership of designing scalable and efficient solutions.
• Full-Stack Development Leadership:
• Proficient in full-stack development, spanning frontend (HTML, CSS, JavaScript) and backend (Django, Flask, Spring Boot), with hands-on experience integrating AI technology into full-stack projects.
• Demonstrated leadership in guiding teams through the integration of AI tech into complex full-stack applications.
• Open-Source Contribution and Community Leadership:
• Valued contributions to open-source AI projects, showcasing leadership in driving innovation and collaboration within the AI community.
• Experience in leveraging open-source AI frameworks to deliver cutting-edge solutions, fostering a culture of sharing and learning within the organization.
• Problem-Solving and Optimization Skills:
• Demonstrated strength in problem-solving and analytical skills, with a track record of optimizing AI algorithms for performance and scalability.
• Leadership in driving continuous improvement initiatives, enhancing the efficiency and effectiveness of AI solutions.

Preferred Technical and Professional Expertise

• Leadership in AI/ML and Data Science:
• Over 12 years of demonstrated leadership in AI/ML and Data Science, driving the development and deployment of AI models in production environments with a focus on scalability, reliability, and efficiency.
• Ownership mentality, ensuring tasks are driven to completion with precision and attention to detail.
• Algorithm Implementation Mastery and Optimization:
• Proven track record of hands-on implementation and optimization of machine learning algorithms, neural networks, and statistical modeling techniques, showcasing expertise in solving complex problems effectively.
• Leadership in guiding teams through algorithm implementation and optimization processes, ensuring tasks are completed with efficiency and accuracy.
• Development of Large Language Models (LLMs):
• Hands-on experience in the development and deployment of large language models (LLMs) in production environments, demonstrating proficiency in distributed systems, microservice architecture, and REST APIs.
• Leadership in owning the end-to-end development process of LLMs, from ideation to deployment, ensuring seamless integration into production workflows.
• MLOps Integration Leadership:
• Experience leading cross-functional teams in the integration of MLOps pipelines with CI/CD tools for continuous integration and deployment, driving the seamless integration of AI/ML models into production workflows.
• Ownership of the MLOps integration process, ensuring tasks are completed on schedule and to the highest standards of quality.
• Commitment to Continuous Learning and Contribution:
• Demonstrated dedication to continuous learning and staying updated with the latest advancements in AI/ML technologies.
• Proven ability to contribute actively to the development and improvement of AI frameworks and libraries, showcasing leadership in driving innovation within the organization.
• Effective Communication and Collaboration:
• Strong communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
• Excellence in interpersonal skills, fostering collaboration and teamwork across diverse teams to drive projects to successful completion.