CommerceIQ
About this role
CommerceIQ builds the AI platform that runs retail and ecommerce operations for some of the world's largest brands, shipping AI agents for content, media and sales into Fortune 100 workflows. This Lead Data Scientist seat is an applied machine learning role at the deep end: training and fine tuning large scale models (LLMs, transformers, diffusion models), using parameter efficient fine tuning methods like LoRA, adapters and quantization aware training, and working across the Hugging Face, PyTorch and TensorFlow ecosystem. Lead here means individual contributor seniority, not people management. The stated bar is 5+ years of hands on applied ML and data science. It is based in Bengaluru. Good fit for a machine learning engineer or scientist who wants to put modern model training and fine tuning into production for enterprise scale customers rather than run experiments that never ship.
Who this is for
What the posting asks for:
- 5+ years of hands on experience in applied machine learning and data science.
- A degree in Computer Science, Machine Learning, Data Science, Statistics or a related field.
- A strong background in machine learning, deep learning and NLP, with proven experience training and fine tuning large scale models (LLMs, transformers, diffusion models).
- Hands on expertise with parameter efficient fine tuning (LoRA, prefix tuning, adapters, quantization aware training).
- Proficiency in PyTorch, TensorFlow and the Hugging Face ecosystem, plus a basic understanding of MLOps (experiment tracking, model monitoring).
Nice to have: distributed training frameworks such as DeepSpeed, PyTorch Lightning or Ray.
The day to day: you build and fine tune large models for production, apply efficient fine tuning and quantization techniques, and ship AI capabilities into the workflows of large brand customers.
Location: Bengaluru.
Honest read: a hands on applied ML role, senior individual contributor, at a company shipping AI into enterprise commerce. Lead is a seniority marker here, not a management title. Strong for someone who wants modern model training work that reaches production.
- 5+ years of hands on experience in applied machine learning and data science.
- A degree in Computer Science, Machine Learning, Data Science, Statistics or a related field.
- A strong background in machine learning, deep learning and NLP, with proven experience training and fine tuning large scale models (LLMs, transformers, diffusion models).
- Hands on expertise with parameter efficient fine tuning (LoRA, prefix tuning, adapters, quantization aware training).
- Proficiency in PyTorch, TensorFlow and the Hugging Face ecosystem, plus a basic understanding of MLOps (experiment tracking, model monitoring).
Nice to have: distributed training frameworks such as DeepSpeed, PyTorch Lightning or Ray.
The day to day: you build and fine tune large models for production, apply efficient fine tuning and quantization techniques, and ship AI capabilities into the workflows of large brand customers.
Location: Bengaluru.
Honest read: a hands on applied ML role, senior individual contributor, at a company shipping AI into enterprise commerce. Lead is a seniority marker here, not a management title. Strong for someone who wants modern model training work that reaches production.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.