Vacancy description
Tredence Inc.
India, Bengaluru
Senior AI/ML Specialist in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
Role description
Senior AI Engineer – Generative AI (GenAI) + Cloud (AWS/GCP/Azure)
We are seeking a Senior AI Engineer with deep expertise in Generative AI (GenAI) and hands-on experience deploying solutions on cloud platforms (AWS, GCP, or Azure). This role focuses on building scalable, production-ready GenAI systems, integrating LLMs into enterprise applications, and optimizing performance in cloud-native environments. You will collaborate with data scientists, product managers, and engineering teams to operationalize cutting-edge AI/ML innovations.
Key Responsibilities
Design and deploy GenAI solutions leveraging LLMs (e.g., GPT, LLaMA, Claude, PaLM) for enterprise use cases such as summarization, content generation, semantic search, and conversational AI.
Implement RAG pipelines using frameworks like LangChain, LlamaIndex, and vector databases (FAISS, Pinecone, Weaviate).
Architect scalable AI systems on cloud platforms (AWS Sagemaker, GCP Vertex AI, or Azure Machine Learning) using services such as BigQuery, DynamoDB, Kubernetes (EKS/GKE/AKS), and serverless functions.
Collaborate with cross-functional teams to productionize models, ensuring robust CI/CD pipelines, monitoring, and automated retraining.
Optimize model serving for latency, throughput, and cost efficiency in cloud environments.
Integrate GenAI APIs (OpenAI, Anthropic, Google Cloud GenAI, Azure OpenAI) into enterprise applications and co-pilot solutions.
Establish MLOps best practices for observability, reproducibility, and secure deployment of GenAI workloads.
Stay updated on GenAI research , tools, and cloud advancements to continuously improve system capabilities.
Required Skills and Experience
Master's or PhD in Computer Science, Machine Learning, or related field.
Experience with cloud-native GenAI APIs (Azure OpenAI, Google Gemini, AWS Bedrock).
Background in building chatbots, copilots, or enterprise-grade GenAI applications.
Contributions to open-source projects in GenAI or cloud ML ecosystems.
Knowledge of security, compliance, and governance for AI workloads in cloud environments.
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