AI ML Engineer
Tata Consultancy Services
Location
🇮🇳 India
Type
Full-time
Salary
Undisclosed
Posted
3d ago
Job Description
TCS Hiring for AI ML Engineer Experience Range: - 05 To 10 Years (Mandatory) (Note: Candidates below 5 years of IT experience shall not be considered) Job Locations : Chennai, Bengaluru, Hyderabad, Pune, Kochi
JOB DESCRIPTION
The
job description
includes developing, testing, and deploying AI/ML models and applications, often using cloud services and generative AI models.
Key responsibilities
involve data preprocessing, model optimization, and collaborating with cross-functional teams to ensure production-ready quality in applications that can include deep learning, chatbots, and image processing. Core
responsibilities
: • Design, build, and maintain machine/ deep learning systems and applications. • Develop and implement AI solutions using tools like deep learning, neural networks, and generative AI models. • Clean, preprocess, and analyze large datasets to ensure data quality and integrity. • Optimize AI algorithms for performance and scalability. • Deploy models into production environments and manage application pipelines. • Collaborate with other teams, including data scientists, engineers, and product managers, to define
requirements
and troubleshoot issues. • Conduct research on emerging AI technologies and best practices.
Required skills
and experience 1) Technical Proficiency: Expertise in programming languages like Python, and machine learning libraries such as scikit-learn, TensorFlow, PyTorch and LangChain. 2) Machine Learning & Statistics: Strong understanding of statistical analysis, machine learning, vectorization, retrieval augmented generation, Gen AI concepts and model evaluation. 3) Data Handling: Experience with data manipulation, feature engineering, and handling large datasets. 4) Software Engineering: Knowledge of software architecture, data structures, and algorithms. 5) Cloud & AI: Experience with cloud AI services (e.g., Google Cloud ML, AWS) and deploying models in cloud or on-prem environments.