Data Scientist Gen AI Engineer

🚀 Mega Walk-In Drive – Data Science, GenAI (5-12 Years) & MLOps Roles (3–12 Years Experience)

📍 Location : Kolkata

📅 Date : Saturday, 15th November

🕤 Time : 9 : 30 AM onwards

📧 Contact Person : Purbita Mondal – purbita.mondal@ltilmindtree.com

🔍 We’re Hiring For :

Data Scientists

GenAI Engineers

MLOps Engineers

Data Scientists with Gen AI :

✅ Mandatory Skills

Data Science, GenAI, Python, RAG

Cloud : Azure / AWS / GCP

AI / ML, NLP

🔸 Preferred Skills

LangChain, ChatGPT, Prompt Engineering

Vector Stores, LLaMA, PaLM, BERT, GPT, BLOOM

Deep Learning, OCR, Transformers

Regression, Forecasting, Classification

MLOps, Model Training, Deployment, Inference

CI / CD, Model Monitoring, Hyperparameter Tuning

Tools : MLflow, Kubeflow, Airflow, Docker, Kubernetes

🧠 Ideal Candidate Profile

5–12 years of experience in Data Engineering, Data Science, AI / ML, or MLOps

Strong grasp of ML algorithms : GPTs, CNN, RNN, SVM, etc.

Experience with BI tools (Power BI, Tableau), data frameworks (Hadoop, PySpark)

Familiarity with TensorFlow, PyTorch, Keras, NumPy, Pandas

Experience with cloud-native development and deployment

Hands-on with NoSQL databases (MongoDB, Cassandra, HBase, Vector DBs)

Excellent communication and analytical skills

MLOPS :

We’re looking for an MLOps Engineering Specialist who is experienced in designing and implementing ML applications at scale in production for our ML Engineering team- The team is a cross-functional team and has ML Engineers and AI Engineers, and closely works with data scientists and data engineers in designing, building and operationalizing AI / ML models-

Roles and Responsibilities :

As an ML Engineering Specialist, you will be owning responsibility to

• operationalize ML models, NLP, Computer Vision, and other type of models-
• End to End model lifecycle management, starting from feature extraction to monitor machine learning models using high end tools and technologies-
• Design & implementation of DevOps principles in Machine Learning
• Model quality assurance, governance, and monitoring
• Integrate models as part of business applications via APIs-
• Execute best practices in version control and continuous integration / delivery-
• Collaborate with data scientists, engineers, and other key stakeholders-
• Work well in a fast-paced cross-functional environment

Mandatory Skills / Requirements :

🌟 Why Join Us?

Work on cutting-edge GenAI and LLM projects

Build scalable AI / ML pipelines and deploy models in production

Collaborate with a fast-paced, innovative team

Flexible work culture and continuous learning

📩 Walk in with your resume and be part of the future of AI!

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