LTIMindtree
Website:
ltimindtree.com
Job details:
Job Summary
We are looking for a highly skilled and experienced Data Science Specialist with strong expertise in Python, Traditional Machine Learning, and Generative AI technologies.
The ideal candidate should have hands-on experience in building, deploying, and evaluating production-grade Gen AI solutions along with a solid understanding of statistical concepts, MLOps practices, and cloud-native deployment environments.
Key Responsibilities
- Design, develop, and deploy scalable machine learning and Generative AI solutions for enterprise use cases.
- Build and optimize traditional machine learning models using Python and relevant ML frameworks.
- Work on production-grade Gen AI applications including Retrieval-Augmented Generation (RAG) systems and LLM-powered solutions.
- Develop and implement evaluation methodologies for Gen AI systems using benchmark datasets and ground truth-based evaluation techniques.
- Utilize evaluation frameworks such as RAGAS, DeepEval, and LLM-as-a-Judge approaches to assess model quality, relevance, and performance.
- Collaborate with cross-functional teams including engineering, product, and business stakeholders to understand requirements and deliver AI-driven solutions.
- Build APIs and deploy AI/ML services using FastAPI and containerized environments.
- Manage deployments using Docker and Kubernetes for scalable and reliable production environments.
- Work on CI/CD pipelines to automate model deployment, testing, and monitoring workflows.
- Monitor and maintain LLM applications using observability and monitoring tools to ensure performance, reliability, and governance.
- Perform statistical analysis and data preprocessing to improve model accuracy and business outcomes.
- Stay updated with the latest advancements in AI/ML, Generative AI, and MLOps technologies.
Required Skills & Qualifications
- 6 to 8 years of experience in Data Science, Machine Learning, or AI-related roles.
- Strong programming expertise in Python.
- Hands-on experience with traditional Machine Learning algorithms and frameworks.
- Strong understanding of statistics and data analysis concepts.
- Proven experience in delivering production-grade Generative AI projects.
- Familiarity with Gen AI evaluation frameworks such as RAGAS, DeepEval, and LLM adjudication methodologies.
- Experience with benchmark dataset evaluation and ground truth validation techniques.
- Strong knowledge of Docker, Kubernetes, and containerized application deployment.
- Experience in developing APIs using FastAPI.
- Understanding of CI/CD pipelines and DevOps practices.
- Exposure to LLM monitoring and observability platforms/tools.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Understanding of vector databases, embeddings, and RAG architectures.
- Familiarity with MLOps and AI governance practices.
- Exposure to enterprise-scale AI deployments and performance optimization.
(ref:hirist.tech)
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