2 - 6 years
4 - 8 Lacs
Posted:2 weeks ago|
Platform:
Work from Office
Full Time
Key Responsibilities: Cloud AI Design and Development: Design, develop, and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Agentic AI: Develop and integrate agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Design and implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Implement robust security measures for cloud-based LLMs, including data encryption, IAM policies, network security, model watermarking, and compliance with cloud security best practices. Technical Leadership: Provide technical guidance and support to junior team members on cloud AI implementation, ensuring high-quality deliverables and adherence to best practices. Client Engagement: Collaborate with clients to understand their AI requirements, develop tailored solutions, and deliver high-quality results. Cloud Solution Architecture: Design scalable, efficient, and cost-effective cloud-based AI/GenAI architectures, considering factors like data quality, model performance, and serverless/container-based deployment options. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation: Ensure thorough testing and validation of AI/GenAI models, including performance evaluation, bias detection, and explainability. Deployment and Maintenance: Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Knowledge Sharing: Share knowledge and expertise with the team, contributing to the development of best practices and staying up-to-date with industry trends. Requirements: Education: Bachelor/Master's in Computer Science, AI, ML, or related fields. Experience: 8+ years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving: Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends
NTT DATA, Inc.
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