Data Scientist - Level 3

Job Description

As a Data Scientist Level 3 at our company, you will have the opportunity to work on cutting-edge technologies and collaborate with cross-functional teams to design and deploy advanced AI solutions. Your primary responsibilities will include designing and deploying machine learning, deep learning, and NLP/LLM models, building scalable ML pipelines on cloud platforms, implementing robust NLP workflows, and ensuring end-to-end model development and deployment. Additionally, you will be expected to stay updated with the latest AI/ML research and provide occasional mentoring to junior team members.Key Responsibilities:- Design, develop, and deploy advanced machine learning, deep learning, and NLP/LLM models for enterprise use cases.- Build and optimize RAG pipelines, embeddings, vector search, and LLM-based solutions end-to-end.- Develop scalable ML and data pipelines using Azure, GCP, and/or AWS cloud services.- Implement robust NLP and conversational AI workflows, including intent understanding, entity extraction, and generative responses.- Own end-to-end model development: data exploration, feature engineering, training, evaluation, optimization, and deployment.- Implement strong MLOps practices (CI/CD, monitoring, model versioning, retraining, containerization).- Work hands-on with Docker/Kubernetes to build scalable, reproducible AI services.- Collaborate with backend teams to integrate ML models into production systems via REST APIs or microservices.- Prepare clear documentation, communicate technical insights, and support stakeholder discussions.- Stay updated with the latest AI/ML research, LLM tooling, cloud capabilities, and best practices.- Provide occasional mentoring or technical guidance to junior data science team members.Qualifications Required:- 57 years of strong, hands-on experience in Data Science and ML/AI development.- Deep practical expertise in ML algorithms, deep learning, NLP, and LLMs (fine-tuning, prompt engineering, RAG).- Solid coding experience in Python and familiarity with frameworks like PyTorch, TensorFlow, scikit-learn.- Strong experience with cloud platforms: Azure, GCP, and/AWS (AI/ML services, deployments, storage, compute).- Hands-on experience with Docker, Kubernetes, CI/CD workflows, and MLOps tooling.- Experience building production-grade ML APIs and integrating models with backend systems.- Strong understanding of data engineering concepts, distributed computing (Spark/Databricks), and model optimization.- Excellent documentation, analytical thinking, and communication skills. As a Data Scientist Level 3 at our company, you will have the opportunity to work on cutting-edge technologies and collaborate with cross-functional teams to design and deploy advanced AI solutions. Your primary responsibilities will include designing and deploying machine learning, deep learning, and NLP/LLM models, building scalable ML pipelines on cloud platforms, implementing robust NLP workflows, and ensuring end-to-end model development and deployment. Additionally, you will be expected to stay updated with the latest AI/ML research and provide occasional mentoring to junior team members.Key Responsibilities:- Design, develop, and deploy advanced machine learning, deep learning, and NLP/LLM models for enterprise use cases.- Build and optimize RAG pipelines, embeddings, vector search, and LLM-based solutions end-to-end.- Develop scalable ML and data pipelines using Azure, GCP, and/or AWS cloud services.- Implement robust NLP and conversational AI workflows, including intent understanding, entity extraction, and generative responses.- Own end-to-end model development: data exploration, feature engineering, training, evaluation, optimization, and deployment.- Implement strong MLOps practices (CI/CD, monitoring, model versioning, retraining, containerization).- Work hands-on with Docker/Kubernetes to build scalable, reproducible AI services.- Collaborate with backend teams to integrate ML models into production systems via REST APIs or microservices.- Prepare clear documentation, communicate technical insights, and support stakeholder discussions.- Stay updated with the latest AI/ML research, LLM tooling, cloud capabilities, and best practices.- Provide occasional mentoring or technical guidance to junior data science team members.Qualifications Required:- 57 years of strong, hands-on experience in Data Science and ML/AI development.- Deep practical expertise in ML algorithms, deep learning, NLP, and LLMs (fine-tuning, prompt engineering, RAG).- Solid coding experience in Python and familiarity with frameworks like PyTorch, TensorFlow, scikit-learn.- Strong experience with cloud platforms: Azure, GCP, and/AWS (AI/ML services, deployments, storage, compute).- Hands-on experience with Docker, Kubernetes, CI/CD workflows, and MLOps tooling.- Experience building production-grade ML APIs and integrating models with backend systems.- Strong understa

Keyskills :
machine learningdeep learningPythonmodel developmentAzureGCPAWSDockerKubernetesmicroservicesdocumentationmonitoringcontainerizationstoragedistributed computingcommunication skillsNLPLLMscloud platformsendtoend deploymentRAG pipelines