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Tier-1 employer, metro role, mid-level and broad AI skillset increases applicant competition.
Strong ML/AI specialization favors candidates with technical ML backgrounds but skills are transferable across industries.
Explicit 2-4 years plus mandatory generative AI, LLM, Python, cloud, Docker/Kubernetes skills make filters high.
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Design, develop, and implement generative AI models (GANs, VAEs, Transformers) across various media types.
Build and optimize scalable Python pipelines for training, fine-tuning, and deploying large language models and generative AI architectures.
Collaborate with cross-functional teams to integrate AI models into products, optimize performance, and mentor junior engineers.
2-4 years of work experience.
Strong proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, Hugging Face Transformers.
Solid understanding and hands-on experience with generative AI models including GANs, VAEs, autoregressive, and diffusion models.
Educational qualification: BE/BTech/MBA/MCA/CA.
Experienced in end-to-end AI model deployment pipelines including cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
Familiar with prompt engineering and large-scale LLMs (e.g., GPT, T5, BERT), reinforcement or unsupervised learning techniques, and MLOps/CI/CD tools.
Demonstrated ability to write efficient, optimized code with a focus on model robustness, scalability, and collaboration with cross-disciplinary teams.