🚀 We're Hiring: AI & Machine Learning Engineer (Senior Level)
Are you an experienced AI professional looking to architect large-scale predictive models and cloud-native machine learning pipelines? NTT Data is actively seeking a highly skilled and analytical Senior AI & Machine Learning Engineer. This premium role offers the flexibility to work across multiple major IT hubs in India, including Noida, Pune, Bangalore, Hyderabad, and Chennai. You will lead the development of enterprise-grade AI applications, optimize deep learning infrastructures, and spearhead product automation deployment frameworks.
Hiring for NTT Data.
💼 Position Overview:
• Role: Senior AI & Machine Learning Engineer
• Experience Required: 5+ Years of industry experience in AI/ML production environments
• Locations: Noida, Pune, Bangalore, Hyderabad, and Chennai (Hybrid / Office Options Available)
• Employment Type: Full-Time, Permanent
• Salary Framework: ₹18,00,000 - ₹32,00,000 Per Annum (Based on expertise evaluation and corporate bands)
• Role: Senior AI & Machine Learning Engineer
• Experience Required: 5+ Years of industry experience in AI/ML production environments
• Locations: Noida, Pune, Bangalore, Hyderabad, and Chennai (Hybrid / Office Options Available)
• Employment Type: Full-Time, Permanent
• Salary Framework: ₹18,00,000 - ₹32,00,000 Per Annum (Based on expertise evaluation and corporate bands)
⚙️ Core Roles & Responsibilities:
As a Senior AI/ML Engineer at NTT Data, your core day-to-day architectural and engineering tasks will include:
• Designing, training, evaluating, and deploying production-ready machine learning and deep learning models.
• Architecting cloud-native MLOps automation pipelines to ensure continuous model evaluation, tracking, and seamless version control.
• Building, packaging, and micro-orchestrating containerized ML microservices behind highly secure RESTful APIs.
• Monitoring distributed infrastructure, optimizing cloud compute resources, and debugging data pipelines for maximum scalability.
• Collaborating with cross-functional engineering units, data scientists, and DevOps architects to deploy code patches securely.
• Implementing robust version control workflows, automated data preprocessing, and model tracking protocols.
As a Senior AI/ML Engineer at NTT Data, your core day-to-day architectural and engineering tasks will include:
• Designing, training, evaluating, and deploying production-ready machine learning and deep learning models.
• Architecting cloud-native MLOps automation pipelines to ensure continuous model evaluation, tracking, and seamless version control.
• Building, packaging, and micro-orchestrating containerized ML microservices behind highly secure RESTful APIs.
• Monitoring distributed infrastructure, optimizing cloud compute resources, and debugging data pipelines for maximum scalability.
• Collaborating with cross-functional engineering units, data scientists, and DevOps architects to deploy code patches securely.
• Implementing robust version control workflows, automated data preprocessing, and model tracking protocols.
📌 Technical Skills & Ecosystem Required:
Candidates applying for this senior engineering position must possess advanced expertise in:
• Programming & Libraries: Strong core programming fundamentals using Python along with its data science ecosystem (NumPy, Pandas, Scikit-Learn).
• Deep Learning: Extensive hands-on experience with deep learning framework architectures (PyTorch or TensorFlow).
• Infrastructure & Scale: Proven production-level containerization experience using Docker and Kubernetes cluster orchestration.
• Cloud Platforms: Solid architectural exposure to Cloud platforms (specifically Azure AI / AWS ML tools) and microservices pattern design.
• MLOps Tooling: Practical implementation tracks with automated MLOps pipelines using orchestration systems like MLflow or Kubeflow.
• Database & Data Versioning: Advanced engineering logic with relational/non-relational database query tuning, scaling, and data versioning tools (DVC).
Candidates applying for this senior engineering position must possess advanced expertise in:
• Programming & Libraries: Strong core programming fundamentals using Python along with its data science ecosystem (NumPy, Pandas, Scikit-Learn).
• Deep Learning: Extensive hands-on experience with deep learning framework architectures (PyTorch or TensorFlow).
• Infrastructure & Scale: Proven production-level containerization experience using Docker and Kubernetes cluster orchestration.
• Cloud Platforms: Solid architectural exposure to Cloud platforms (specifically Azure AI / AWS ML tools) and microservices pattern design.
• MLOps Tooling: Practical implementation tracks with automated MLOps pipelines using orchestration systems like MLflow or Kubeflow.
• Database & Data Versioning: Advanced engineering logic with relational/non-relational database query tuning, scaling, and data versioning tools (DVC).
📋 Selection & Interview Process:
• Phase 1: Technical CV Evaluation – Initial screening focused on past product delivery patterns and scale implementations.
• Phase 2: System Design & Coding Test – A time-bound practical machine coding assignment evaluating pipeline orchestration, heavy data preprocessing workflows, and ML logic patterns.
• Phase 3: Architectural Panel Deep Dive – An intricate face-to-face evaluation covering cloud microservices, MLOps scalability metrics, and distributed cluster resource monitoring.
• Phase 4: HR & Leadership Round – Final strategic conversation focusing on corporate band structure alignment, local hub matching, and onboarding workflows.
• Phase 1: Technical CV Evaluation – Initial screening focused on past product delivery patterns and scale implementations.
• Phase 2: System Design & Coding Test – A time-bound practical machine coding assignment evaluating pipeline orchestration, heavy data preprocessing workflows, and ML logic patterns.
• Phase 3: Architectural Panel Deep Dive – An intricate face-to-face evaluation covering cloud microservices, MLOps scalability metrics, and distributed cluster resource monitoring.
• Phase 4: HR & Leadership Round – Final strategic conversation focusing on corporate band structure alignment, local hub matching, and onboarding workflows.
🎁 Perks & Benefits:
• Geographic Mobility: Flexible options to operate from premier tech offices in Noida, Pune, Bangalore, Hyderabad, or Chennai.
• Elite Compensation Structure: Highly lucrative premium salary packages (₹18L - ₹32L PA) that mirror your core senior impact values.
• Advanced Compute Resources: Direct access to bleeding-edge production environments and high-scale cloud clusters.
• Collaborating Framework: Join forces with top-tier data engineers, tech directors, and innovation leads across India.
• Geographic Mobility: Flexible options to operate from premier tech offices in Noida, Pune, Bangalore, Hyderabad, or Chennai.
• Elite Compensation Structure: Highly lucrative premium salary packages (₹18L - ₹32L PA) that mirror your core senior impact values.
• Advanced Compute Resources: Direct access to bleeding-edge production environments and high-scale cloud clusters.
• Collaborating Framework: Join forces with top-tier data engineers, tech directors, and innovation leads across India.
📩 How to Apply:
Know an experienced engineering professional looking to scale their AI/ML skills across India's top tech hubs? Share this premium career opportunity with them!
