Model Development :
- Design, build, and deploy production-grade AI / ML solutions with a focus on scalable, real-world applications.
Programming & Data Handling :
Develop and implement machine learning models using Python, PySpark, SQL, and popular ML libraries such as Scikit-learn, XGBoost, and LightGBM.Cloud ML Platforms :
Build and manage cloud-native ML solutions using platforms like AWS SageMaker, GCP Vertex AI, or Azure ML.NLP & GenAI Expertise :
Apply strong knowledge in natural language processing and generative AI frameworks including Hugging Face, LangChain, and LlamaIndex.MLOps & Deployment :
Utilize MLOps tools such as MLflow, Weights & Biases, and DVC for model tracking and versioning. Deploy models using FastAPI, Flask, Docker, and Kubernetes.Vector Databases & Advanced Use Cases :
Work with vector databases to enable semantic search and other advanced GenAI use cases.Text-to-SQL Integration :
Apply familiarity with SQL Coder or Text-to-SQL models to integrate natural language interfaces with structured data sources.Stakeholder Collaboration :
Communicate effectively with stakeholders, translate business problems into technical solutions, and collaborate closely with cross-functional teams.Education and Work Experience :
B.E / B.Tech or equivalent degree in Computer Science, Information Technology, or a related field3–5 years of hands-on experience in developing and deploying AI / ML solutions in production environmentsSpecialized Knowledge, Skills, and Abilities :
Proficiency in Python, PySpark, and SQLExperience with Scikit-learn, XGBoost, LightGBMStrong hands-on experience with AWS SageMaker, GCP Vertex AI, or Azure MLDeep understanding of NLP / GenAI technologies : Hugging Face, LangChain, LlamaIndexWorking knowledge of MLOps tools : MLflow, Weights & Biases, DVCFamiliarity with deployment using FastAPI, Flask, Docker, KubernetesExperience with Vector Databases and Text-to-SQL modelsExcellent communication, stakeholder engagement, and team collaboration skillsSkills Required
Python, Pyspark, Sql, XGBoost