Role Proficiency:

Design and develop ML solutions that will enable intelligent experiences and provide value. Collaboratively work with business technology and product teams to understand the product objectives and formulate the ML problem under minimal guidance from Lead II

Outcomes:

      Executes relevant data wrangling activities related to the problem       Conduct ML experiments to understand feasibility; building baseline models to solve the business problem       Fine tune the baseline model for optimum performance       Test Models internally per acceptance criteria from the business       Identify areas and techniques to optimize the model based on test results       Document relevant artefacts for communicating with the business       Work with data scientists to deploy the models.       Work with product teams in planning and execution of new product releases.       Set OKRs and success steps for self/ team and provide feedback of goals to team members   Identify metrics for validating the models and communicate the same in business terms to the product teams.   Keep track of the trends and do rapid prototyping to understand the feasibility of utilizing in existing solutions

Measures of Outcomes:

      Selection of right algorithms for the business problems       Successful deployment of the model with optimised accuracy for baseline model       Number of time project schedule / timelines adhered to       Personal and team achievement of quarterly/yearly objectives (OKR Assignments HIG Stretch goals)       Number of internal testing observations published and models refined to achieve 100 % business objectives with mentoring from the Lead ML Engineer       Number of business metric and corresponding model metrics identified independently or with assistance from product team / ML Specialist       Number of areas identified for improving the model using new technologies for product / feature improvements Number of Rapid prototypes using state of the art methods

Outputs Expected:

Design to deliver Product Objectives:

Design ML solutions which are aligned to and achieve product objectives Understand the business requirements; formulate into an ML problem Define data requirements for the model building and model monitoring; working with product managers to get necessary data Define the data requirement for the problem Define the AI scope and metrics from the product and business objectives with guidance from Lead II Identify technology components for Rapid prototype Alignment of Business metrics to Model Metrics Check the validity of the training data and test data requirements from the performance standpoint and take necessary actions

Updated on state of art techniques in the area of AI / ML :

Perform necessary research to use the latest state of the art techniques to design scalable approaches Explain the relevance of the technologies
its pros and cons to the product team to enable appropriate design experiences

Skill Examples:

     Technically strong with the ability to connect the dots      Ability to communicate the relevance of technology to the stakeholders in a simple and relatable language      Capability in selecting the appropriate techniques based on the data availability and set expectations on the overall functionality of the solutions      Ability to understand the limitations of the current technology; defining the AI scope and metrics      Curiosity to learn more about new business domains and Technology Innovation An empathetic listener who can give and receive honest thoughtful feedback

Knowledge Examples:

      Expertise in machine learning model building lifecycle       Clear understanding of various ML techniques and its appropriate use to business problems       A strong background of Statistics and Mathematics       Expertise in one of the domains – Computer Vision Language Understanding or structured data       Experience in executing collaboratively with engineering design user research teams and business stakeholders       Experience with data wrangling techniques preprocessing and post processing requirements for ML solutions       Aware of the techniques of validating the quality of the data       Experience in identifying the testing criteria to validate the quality of the model output       Good knowledge python and deep learning frameworks like Tensorflow Pytorch Caffe   Familiar with the machine learning model testing approaches A genuine eagerness to work and learn from a diverse and talented team

Additional Comments:

Job Description: We are seeking an experienced AI Lead with a minimum of 10 years of industry experience in the field of Artificial Intelligence. The ideal candidate will have a proven track record of successfully leading and delivering multiple projects in Machine Learning, Deep Learning, and Natural Language Processing (NLP). Additionally, they should possess sound knowledge in Generative AI and Large Language Models (LLMs). Responsibilities: • Project Leadership: Lead end-to-end AI projects, from conception to delivery, ensuring alignment with business objectives and stakeholder requirements. • Technical Expertise: Serve as a subject matter expert in AI, providing guidance and support to the team in the development and implementation of advanced machine learning and deep learning models. • Research and Development: Stay abreast of the latest advancements in AI technologies and methodologies, conducting research and experiments to drive innovation and enhance project outcomes. • Team Management: Manage and mentor a team of junior data scientists and machine learning engineers, providing technical guidance, coaching, and professional development opportunities. • Collaboration: Collaborate closely with cross-functional teams, including product management, engineering, and business development, to identify opportunities for leveraging AI to solve business challenges and drive growth. • Quality Assurance: Ensure the quality and accuracy of AI solutions through rigorous testing, validation, and performance monitoring. • Strategic Planning: Contribute to the development of AI strategies and roadmaps, outlining key initiatives and milestones to support business objectives. Qualifications: • Bachelor’s degree in computer science, Engineering, Mathematics, or related field. Advanced degree (Master's or Ph.D.) preferred. • Minimum of 10 years of industry experience in artificial intelligence, with a focus on machine learning, deep learning, and NLP. • Proven track record of leading and delivering multiple AI projects from conception to completion. • Expertise in machine learning frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn. • Expertise in MLOps tools, Databricks, and AI services offered by cloud platforms such as Azure, AWS, and GCP. • Experience with Generative AI and Large Language Models (LLMs) such as GPT, BERT, or Transformer models. • Excellent leadership and communication skills, with the ability to effectively manage and mentor a team of junior data scientists and ML engineers. • Strong analytical and problem-solving skills, with a keen attention to detail and a commitment to delivering high-quality results. • Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities and requirements. Join Our Team: If you are a seasoned AI professional with a passion for innovation and a track record of delivering impactful solutions, we invite you to apply for the AI Lead position. Join us in shaping the future of AI and making a positive impact on businesses and society