Artificial Intelligence Engineer Modus Business Transformation Platform

0.0 - 5.0 years

2 - 7 Lacs

Bengaluru

Hybrid

Design, develop, and implement Graph RAG models to enhance data relationships and knowledge retrieval. Build, train, and fine-tune LLMs to work with Microsoft Co-pilot and Open Azure AI. Utilize the Azure Samples Graph RAG Accelerator to accelerate Required Candidate profile exp in developing and deploying AI models, specifically Graph RAG and LLMs. exp with Microsoft Azure, including Azure AI and related services. Azure Samples Graph RAG Accelerator is highly

Posted 3 months ago

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Software Developer-AI Probus Smart Things

4 - 8 years

8 - 18 Lacs

Noida

Work from Office

3-5 years of experience in data science, research and development. Strong proficiency in Python, R , or other programming languages for data analysis and model development. Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, etc. Experience working with large-scale data processing tools such as Spark, Hadoop , or distributed computing frameworks. Hands-on experience in designing, developing, and training neural network models from scratch , with successful deployment in production environments. Experience in model quantization and optimization for deployment across different CPU/NPU architectures. Knowledge of accelerators across various chipset vendors and their integration for optimizing AI workloads. Deep understanding of statistical modeling, optimization techniques, and AI methodologies. Understanding of various model training, validation and deployment pipelines . Proven track record of published research or contributions to open-source projects will be appreciated. Excellent communication skills and ability to present complex ideas to both technical and non-technical stakeholders.Role & responsibilities Preferred candidate profile

Posted 4 months ago

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Artificial Intelligence Engineer Dwaraka Starline

2.0 - 7.0 years

8 - 18 Lacs

hyderabad

Work from Office

Key Responsibilities: Design AI-driven solutions for core veterinary workflows, such as patient triaging, diagnostics support, treatment plan suggestions, appointment scheduling, and client communications. Develop AI assistants and multi-agent systems to automate routine tasks like SOAP note summarization, clinical documentation (Medical Records), prescription and other reminders, and client follow-ups. Implement RAG pipelines leveraging veterinary knowledge bases, clinical case data, Case Summaries and standard care protocols. Integrate LLMs into practice management modules for intelligent querying, FAQ automation, and veterinary clinical knowledge support. develop and deploy AI services using Azure AI Services , Azure OpenAI , and integrate with Hapivet.ai Ensure secure, compliant, and scalable deployment of AI/ML models in line with veterinary data privacy standards and healthcare regulations. Collaborate with veterinarians, product managers, and software engineers to ensure AI solutions are clinically relevant, user-friendly, and impactful. Required Skillset:Machine Learning & Deep Learning for Healthcare Strong foundation in supervised/unsupervised learning, anomaly detection, and predictive analytics applicable to veterinary clinical data. Experience with CNNs (for imaging), RNNs/LSTMs (for sequential data like patient histories) and Transformers for natural language tasks. Proficiency with TensorFlow , PyTorch , and Hugging Face . Good to have understanding on GANs (medical imaging, data privacy-safe synthetic data, or image-based diagnostics) LLMs & NLP for Veterinary Applications Deep understanding of transformer models ( GPT, BERT, LLaMA ) applied in medical/veterinary text summarization and knowledge extraction. Fine-tuning LLMs with techniques with PEFT , LoRA , QLoRA for domain-specific tasks. Expertise in Prompt Engineering and Chain of Thought (CoT) design for veterinary use cases. RAG pipeline development with veterinary case databases using Pinecone or Azure AI Search . AI Agent Workflows & Orchestration Multi-agent coordination and AI workflow orchestration with LangChain , LangGraph , and Microsoft Autogen SDK . Experience with context management using Model Context Protocol (MCP) in clinical task flows. Cloud AI Deployment & Engineering Experience with Azure AI, model serving (Triton, TensorFlow Serving, TorchServe). CI/CD for AI models, cloud security, and scalable API integration. Programming & Data Engineering Advanced proficiency in Python, R working knowledge of TypeScript . Veterinary data processing experiencehandling EMRs, patient histories, and diagnostic reports Data cleaning, transformation, and ensuring data quality for clinical applications. Preferred Experience: AI/ML deployment in veterinary practice management systems or healthcare applications . Understanding of veterinary compliance, data sensitivity, and client confidentiality (e.g., pet health records, veterinary licensing). Exposure to veterinary-specific AI applications, such as diagnostic imaging analysis , clinical decision support systems , or client interaction bots . Familiarity with DeepSpeed , Megatron-LM , and scaling techniques for LLMs. Soft Skills & Domain Understanding: “Passion for improving pet care and veterinary services through technology”. Strong communication skills for collaborating with veterinary professionals. Ability to translate clinical workflows into AI-enabled solutions.

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