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Tier-1 VC-backed employer, mid-level ML role, and Bangalore metro drive high competition.
Applied ML and LLM skills are transferable, though commerce domain experience favors candidates (medium sensitivity).
Explicit 5+ years, Master's/PhD requirement, and mandatory advanced ML/LLM skills make filters strict.
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Own development and fine-tuning of large-scale AI models (LLMs, transformers, etc.) for domain-specific applications.
Lead and mentor a team of applied scientists and ML engineers to deliver scalable AI solutions.
Collaborate cross-functionally with product, engineering, and business teams to implement impactful AI innovations.
Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or related field.
5+ years of hands-on experience in applied machine learning and data science.
Proven experience with machine learning frameworks such as PyTorch, TensorFlow, and Hugging Face ecosystem.
Demonstrated skills in fine-tuning foundation models using PEFT approaches like LoRA, prefix tuning, adapters, and quantization-aware training.
Experienced leader capable of mentoring technical applied science teams and guiding innovation.
Strong expertise in adapting foundation models to domain-specific problems with robust validation and performance optimization.
Proficient in practical deployment of ML solutions including MLOps, working with large datasets, and model scaling on cloud or HPC environments.