Tata Consultancy Services
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Hyderabad · On-site · Sep 30
Software Development · 10000+ Employees · Mumbai, India
Hiring: Engineering
What employees say
+ Good work life balance and nice work environment.
− Low hike not more than 7%
More reviews on the company profile.
Interview experience · Data Analyst
2 rounds. 1st round technical power bi and sql like cumulative total. What data sources you used. few scenario based questions, remove duplicate in sql. Optimization of slow performing report
Average difficulty · India · 22,544 reports
More interview insightsJob description
Overview
The AWS AI/ML Engineer is responsible for designing, building, deploying, and scaling AI and Machine Learning solutions on AWS.
Responsibilities
- Design and develop machine learning models for classification, regression, forecasting, NLP, or computer vision use cases
- Build end-to-end ML pipelines (data ingestion, training, validation, deployment) on AWS
- Develop and deploy real-time and batch inference services
- Apply feature engineering, model tuning, and evaluation techniques
- Use Amazon SageMaker for training, tuning, deployment, and monitoring of ML models
- Design scalable architectures using AWS Lambda, ECS/EKS, Step Functions
- Manage data storage and access using S3, DynamoDB, RDS/Aurora
- Ensure availability, performance, and cost optimization of ML workloads
- Implement CI/CD pipelines for ML models and data workflows
- Enable model versioning, monitoring, retraining, and rollback
- Track model performance, drift, and data quality
- Follow best practices for MLOps, automation, and observability
- Adhere to enterprise security, privacy, and compliance standards
- Work closely with data engineers, cloud architects, and business stakeholders
- Translate business problems into AI/ML solutions
- Support POCs, pilots, and production rollouts
- Contribute to reusable ML frameworks and accelerators
Qualifications
- Strong understanding of supervised and unsupervised ML algorithms
- Feature engineering, hyperparameter tuning, model evaluation
- Amazon SageMaker (Studio, Pipelines, Endpoints, Model Monitor)
- Strong proficiency in Python
- Hands-on with scikit-learn, TensorFlow, PyTorch
- REST APIs, inference services using FastAPI / Flask
- SQL and basic data engineering skills
- Data ingestion and transformation pipelines
- S3, Athena, Glue, Redshift (exposure preferred)
- Structured and unstructured data handling
- Knowledge of automation / RPA integrations
- Domain exposure to manufacturing, supply chain, or enterprise IT
Nice to have
- Exposure to Generative AI / LLM-based ML workflows
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Job application FAQ
Last updated 8 October 2026
- How do I apply for Azure ML at Tata Consultancy Services?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Tata Consultancy Services may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Azure ML role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Azure ML remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this Azure ML role at Tata Consultancy Services?
- Key skills for this role include skills listed in the job description. Upload a resume to see which requirements you already meet and which are gaps.