Generative Ai Engineer

17 hours ago

Hosur, India Straive Full time

Role Summary: The Gen AI Lead Developer will play a key role in designing, implementing, and overseeing the development of advanced generative AI models, platforms, and systems. This individual will work closely with data scientists, engineers, and business stakeholders to design AI solutions that drive value and innovation. Experience: 6-13 yearsWork Mode: Hybrid (3 days at office)Location: All Straive Locations Key Responsibilities: Lead the design and development of scalable, high-performance generative AI systems.Architect end-to-end AI solutions, from data collection and preprocessing to model development and deployment.Ensure seamless integration of AI systems into existing platforms, enhancing business functionality.Generative AI Model Development:Lead the design and development of generative AI models, including but not limited to transformers and Large Language Models (LLMs).Collaborate with research teams to keep the organization at the forefront of AI advancements.AI Strategy & Innovation:Stay up-to-date with the latest advancements in generative AI research and technology.Drive innovation in AI strategies, recommending tools, techniques, and approaches to improve performance and capabilities continually.Contribute to the development of AI strategies that align with organizational goals and objectives. Required Skills & Experience: Proven experience in AI/ML model development, with a focus on generative models such as LLM, transformers.Strong experience in MLOps, Agentic AI and RAG.Strong experience designing and deploying scalable AI architectures in the cloud environments (AWS/Azure/GCP)Experience with AI frameworks and libraries such as Tensor Flow PyTorch.Experience with data engineering and pre-processing for generative models.Deep understanding of deep learning, reinforcement learning, unsupervised learning, and Natural Language Processing (NLP).Proficiency in Python, SQL and other relevant programming languages.Strong knowledge of machine learning pipelines, model versioning, and CI/CD for AI/ML.

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