AI/ML Lead or Architect - S

Tata Consultancy Services; India; Presencial; INR 450.000 - 700.000; Jornada completa

Descripción de la vacante

Tata Consultancy Services is seeking an experienced AI/ML Architect to define and execute strategy across cloud and on‑premises. You will lead architectures for predictive analytics, NLP, CV, and Generative AI, establishing governance, pipelines, and scalable platforms. Strong leadership and hands‑on ML expertise are essential.

You will mentor engineers and collaborate with stakeholders to translate requirements into enterprise solutions, advancing AI adoption across business units.

Formación

• Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, or related field.
• 10+ years of IT experience with 5+ years in AI/ML architecture or leadership roles.
• Strong expertise in ML, DL, statistical modeling and data science methodologies.
• Hands-on experience with AI/ML frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, Hugging Face.
• Strong programming skills in Python, SQL, and Java/Scala/C#.
• Experience with cloud platforms: Azure AI Services, AWS SageMaker, Google Vertex AI.
• Experience with Docker and Kubernetes; knowledge of distributed computing and big data technologies.

Responsabilidades

• Define and execute AI/ML architecture strategies aligned with business objectives.
• Design scalable, secure, and high-performance AI/ML solutions across cloud and on-premises environments.
• Lead architecture of predictive analytics, Generative AI, NLP, CV, recommendations, and MLOps platforms.
• Evaluate emerging AI technologies and recommend adoption strategies.
• Establish AI governance, model lifecycle management, and responsible AI practices.
• Architect end-to-end ML pipelines: data ingestion, feature engineering, training, deployment, monitoring.
• Lead model selection, experimentation, optimization, and tuning.
• Define integration patterns between AI services and enterprise apps.
• Lead and mentor AI Engineers, Data Scientists, ML Engineers, Data Engineers.
• Collaborate with stakeholders to identify AI use cases and translate requirements into solutions.
• Drive architecture reviews, design governance, and executive roadmaps.
• Establish MLOps best practices for CI/CD, versioning, monitoring, retraining.
• Implement model observability, explainability, and performance tracking.
• Ensure scalability, reliability, security, and compliance of AI systems.
• Define standards for AI deployment, testing, and production support.
• Stay current with Generative AI, LLMs, AI Agents; conduct POCs and drive adoption.

Conocimientos

Machine Learning

Deep Learning

Statistical Modeling

Data Science

Python

SQL

Java/Scala/C#

Educación

Bachelor's or Master's degree in CS/AI/Data Science/Engineering

Herramientas

TensorFlow

PyTorch

Scikit-learn

Keras

Hugging Face

Descripción del empleo

Key Responsibilities

AI/ML Strategy & Architecture

• Define and execute AI/ML architecture strategies aligned with business objectives.
• Design scalable, secure, and high-performance AI/ML solutions across cloud and on-premises environments.
• Lead the architecture of predictive analytics, Generative AI, NLP, Computer Vision, Recommendation Systems, and MLOps platforms.
• Evaluate emerging AI technologies and recommend adoption strategies.
• Establish AI governance, model lifecycle management, and responsible AI practices.

Solution Design & Development

• Architect end-to-end machine learning pipelines including data ingestion, feature engineering, model training, deployment, and monitoring.
• Design and implement enterprise AI platforms using Azure AI, AWS AI/ML, Google Cloud AI, OpenAI, Anthropic, or similar ecosystems.
• Lead model selection, experimentation, optimization, and performance tuning.
• Define integration patterns between AI services and enterprise applications.

Leadership & Stakeholder Management

• Lead and mentor AI Engineers, Data Scientists, ML Engineers, and Data Engineers.
• Collaborate with business stakeholders to identify AI use cases and translate requirements into technical solutions.
• Drive technical discussions, architecture reviews, and design governance.
• Present AI solution roadmaps and recommendations to executive leadership.

MLOps & Operational Excellence

• Establish MLOps best practices for CI/CD, model versioning, monitoring, and retraining.
• Implement model observability, explainability, and performance tracking frameworks.
• Ensure scalability, reliability, security, and compliance of AI systems.
• Define standards for AI deployment, testing, and production support.

Innovation & Research

• Stay current with advancements in Generative AI, LLMs, AI Agents, Deep Learning, and emerging AI frameworks.
• Conduct proof-of-concepts (POCs) and innovation initiatives.
• Drive AI adoption across business units and identify opportunities for automation and optimization.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
• 10+ years of IT experience with 5+ years in AI/ML architecture or technical leadership roles.
• Strong expertise in Machine Learning, Deep Learning, Statistical Modeling, and Data Science methodologies.
• Hands-on experience with AI/ML frameworks such as:
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Keras
  • Hugging Face
• Strong programming skills in Python, SQL, and one or more languages such as Java, Scala, or C#.
• Experience with cloud platforms:
  • Microsoft Azure AI Services
  • AWS SageMaker
  • Google Vertex AI
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Knowledge of distributed computing and big data technologies.