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Tier-1 brand, metro location, and mid-level experience range increase candidate density.
ML/AI skills are transferable across industries, but generative AI specialization makes fit moderately sensitive.
Explicit 4-7 years plus mandatory generative AI/LLM, Python, cloud and container skills enforce strict filters.
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Design, develop, and implement generative AI models such as GANs, VAEs, and Transformers for diverse applications including text, image, audio, and video.
Build scalable Python pipelines for training, fine-tuning, and deploying large language models and generative AI architectures, optimizing model performance for speed, accuracy, and resource use.
Collaborate with data scientists, ML engineers, and product teams to integrate AI models into products and platforms; mentor junior engineers and participate in code reviews.
4-7 years of experience in relevant AI/ML development roles.
Strong proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
In-depth knowledge of generative AI models (GANs, VAEs, autoregressive, diffusion models) and experience with large language model (LLM) training and fine-tuning.
Familiarity with cloud platforms (AWS, GCP, Azure), containerization (Docker/Kubernetes), and end-to-end AI model deployment pipelines.
Must have BE/BTech, MBA, MCA, or CA degree.
Experienced working in AI model development and deployment, comfortable optimizing and scaling complex generative models.
Proficient in Python programming and able to collaborate cross-functionally with product and data science teams in a delivery/advisory environment.
Demonstrates capability to mentor junior team members and contribute to code quality and documentation in a fast-paced consulting or managed services context.