High Salary Data Scientist
2 days ago
About the Role Straive is looking for a talented and driven Consultant / Data Scientist / GenAI Engineer to join our Analytics & GenAI delivery team. In this role, you will work under the guidance of the Senior Project Manager / Engagement Manager to design, develop, and deploy advanced AI/ML and Generative AI solutions for global enterprise clients. You will be part of a high-performing team, collaborating with both onshore and offshore members to build scalable, production-grade AI systems. This role is ideal for candidates from premier engineering institutes with 2–3 years of relevant experience in Python development, LLM integration, and RAG workflows, along with a passion for solving complex problems in real-world business contexts. Key Responsibilities - Develop and maintain Python-based applications, AI/ML models, and data processing pipelines for GenAI projects. - Implement Large Language Model (LLM) integrations, including Retrieval-Augmented Generation (RAG) pipelines and embedding-based search solutions. - Build data ingestion and transformation workflows, working with structured and unstructured datasets. - Optimize AI model performance through prompt engineering, fine-tuning, and evaluation techniques. - Collaborate closely with senior team members to translate business requirements into technical solutions. - Integrate AI solutions with vector databases (e.g., Cosmos DB, Pinecone, ChromaDB) and API-driven applications. - (Optional) Contribute to cloud-native deployments and Azure architecture–based solutions, including containerization, CI/CD, and basic MLOps workflows. - Document workflows, maintain code repositories, and follow Agile development practices. Required Qualifications - 2–3 years of relevant experience in AI/ML development, preferably in enterprise projects. - Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field from a premier engineering institute. - Proficiency in Python programming and familiarity with relevant libraries (e.g., LangChain, Hugging Face, Pandas, NumPy). - Hands-on experience implementing RAG pipelines, embeddings, and vector search solutions. - Understanding of LLM architectures and integration patterns. - Working knowledge of SQL and data processing best practices. - Basic knowledge of cloud DevOps concepts, preferably with Azure (AWS/GCP experience is also acceptable). Preferred Skills - Exposure to agentic AI frameworks such as LangGraph, Semantic Kernel, or similar. - Familiarity with ML model lifecycle management and deployment workflows. - Prior experience working with cross-border teams and Agile environments.
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