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 – We’re Hiring For: Data Scientists GenAI Engineers MLOps EngineersData 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 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 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 Tag someone who’d be a great fit or share this opportunity.hashtag#WalkInDrivehashtag#HyderabadJobs hashtag#kolkatajobs hashtag#GenAIhashtag#DataSciencehashtag#MLOpshashtag#AIJobshashtag#MachineLearninghashtag#Hiringhashtag#TechCareershashtag#LangChainhashtag#LLMhashtag#Pythonhashtag#CloudJobshashtag#PromptEngineeringhashtag#ModelDeploymenthashtag#MLflowhashtag#Kubeflow