Data Scientist Gen AI Engineer

Mega Walk-In Drive – Data Science, GenAI (5-12 Years) & MLOps Roles (3–12 Years Experience)Location: KolkataDate: Saturday, 15th NovemberTime: 9:30 AM onwardsContact Person: Purbita Mondal – purbita.mondal@ltilmindtree.comWe’re Hiring For:Data ScientistsGenAI EngineersMLOps EngineersData Scientists with Gen AI:✅ Mandatory SkillsData Science, GenAI, Python, RAGCloud: Azure / AWS / GCPAI/ML, NLPPreferred SkillsLangChain, ChatGPT, Prompt EngineeringVector Stores, LLaMA, PaLM, BERT, GPT, BLOOMDeep Learning, OCR, TransformersRegression, Forecasting, ClassificationMLOps, Model Training, Deployment, InferenceCI/CD, Model Monitoring, Hyperparameter TuningTools: MLflow, Kubeflow, Airflow, Docker, KubernetesIdeal Candidate Profile5–12 years of experience in Data Engineering, Data Science, AI/ML, or MLOpsStrong 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, PandasExperience with cloud-native development and deploymentHands-on with NoSQL databases (MongoDB, Cassandra, HBase, Vector DBs)Excellent communication and analytical skillsMLOPS: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 environmentMandatory Skills/Requirements:• Experience in implementing machine learning life cycle on Azure ML and Azure Databricks along with other Azure services such as Azure DevOps, Azure functions etc-• Experience with Machine learning frameworks, libraries, and agile environments-• Experience implementing Azure Cognitive services in business applications-• Experience with various model deployment strategies• Experience with Python and SQL is must- Understanding of distributed frameworks such as Spark, Dask, Ray etc- is a plus-• Experience with version control tools such as Git, Bitbucket etc-• Knowledge on Docker, Jenkins, Kubernetes, and other DevOps tools-• Knowledge on Infra-as-a-Code via ARM or Terraform templates-• Familiarity with Large Language Models and Operationalization of foundation models on cloud platforms will be a plus-• Outstanding analytical and problem-solving skills-"Why Join Us?Work on cutting-edge GenAI and LLM projectsBuild scalable AI/ML pipelines and deploy models in productionCollaborate with a fast-paced, innovative teamFlexible work culture and continuous learningWalk in with your resume and be part of the future of AITag someone who’d be a great fit or share this opportunity.hashtag#WalkInDrivehashtag#HyderabadJobshashtag#kolkatajobshashtag#GenAIhashtag#DataSciencehashtag#MLOpshashtag#AIJobshashtag#MachineLearninghashtag#Hiringhashtag#TechCareershashtag#LangChainhashtag#LLMhashtag#Pythonhashtag#CloudJobshashtag#PromptEngineeringhashtag#ModelDeploymenthashtag#MLflowhashtag#Kubeflow