GROUP TECHNICAL MANAGER

Job Description (Posting).

A highly skilled and experienced AI / ML Architect to lead the design, development, and deployment of innovative AI / ML solutions. You will be responsible for translating business requirements into scalable, robust, and production-ready AI / ML architectures, primarily leveraging the Google Cloud Platform (GCP). You will be a technical leader, mentoring other engineers and driving best practices in ML Ops.Total Years of Experience : 8-15 YearsRelevant Experience : 7+ Years in AI / ML Architecture and DevelopmentKey Responsibilities : Solution Architecture : Design and architect end-to-end AI / ML solutions tailored to specific business needs, ensuring scalability, performance, and security. Technical Leadership : Provide technical leadership and guidance to a team of AI / ML Engineers, Data Scientists, and Software Engineers. GCP Expertise : Leverage deep knowledge of Google Cloud Platform (GCP) services, including BigQuery, Cloud Composer, Vertex AI, and other AI / ML services, to build and deploy AI / ML models. Model Development & Deployment : Lead the development, deployment, and monitoring of machine learning models, ensuring their reliability and accuracy in production. ML Ops Implementation : Champion and implement ML Ops best practices, including CI / CD pipelines, automated model retraining, and robust monitoring systems. Technology Evaluation : Research and evaluate new AI / ML technologies and frameworks, recommending solutions that align with business goals and technical requirements. Collaboration : Collaborate with cross-functional teams, including product managers, data engineers, and business stakeholders, to define AI / ML strategies and deliver impactful solutions. Performance Optimization : Optimize AI / ML models and infrastructure for performance, cost, and scalability. Data Governance : Adhere to data governance and security policies, ensuring the responsible and ethical use of AI / ML technologies. Documentation : Create and maintain comprehensive documentation for AI / ML architectures, models, and deployment processes. Mentorship : Mentor junior engineers and data scientists, fostering a culture of learning and innovation.Required Skills and Experience : Machine Learning Expertise : Strong understanding of machine learning concepts, including supervised, unsupervised, and reinforcement learning. Programming Proficiency : Expertise in Python and experience with related libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy. Deep Learning : Proven experience in developing and deploying deep learning models using frameworks like TensorFlow or PyTorch. Cloud Platform Experience : Extensive experience with Google Cloud Platform (GCP), including BigQuery, Cloud Composer, Vertex AI, and other AI / ML services. Data Engineering : Solid understanding of data engineering principles and experience with data pipelines and ETL processes. Statistical Analysis : Strong foundation in statistical analysis and data visualization techniques. Model Deployment & Monitoring : Hands-on experience with model deployment and monitoring in a production environment. ML Ops : Deep understanding and practical experience with ML Ops principles and tools, including CI / CD pipelines, model versioning, and automated retraining. Containerization & Orchestration : Experience with containerization technologies (e.g., Docker) and orchestration platforms (e.g., Kubernetes). Communication Skills : Excellent communication, presentation, and interpersonal skills. Problem-Solving Skills : Strong analytical and problem-solving skills with the ability to work independently and as part of a team. Experience in multiple Business Verticals : Experience in Banking / Finance / telecom / Retail / technology etc is a plus. Text Analytics and Text Mini

Qualification

Bachelor of Technology / Engineering

Skill (Primary)

Technical Skills-Cloud Platform-Google Cloud Platform

Skills Required

Tensorflow, Pandas, Numpy, BigQuery, Pytorch, Python, Kubernetes, Docker, Google Cloud Platform