PANIPAT · FULLTIME
Sr Machine Learning Engineer - LLM/SLM
Proffer It Consultancy
Panipat · onsite · Posted 21d ago
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Undisclosed4–9 yrsfulltimePanipat
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Section · 01
About this role
Position Name:Senior Machine Learning Engineer - LLM/SLM
Location: Bangalore, Pune, Gurgaon ( Hybrid)
Experience: 4+ years
About BinQle
BinQle is a global delivery and execution partner supporting enterprises across the US, India, Singapore and Australia. We specialize in structured hiring, managed teams, and long-term delivery support.
Role Summary:
Responsible for fine-tuning transformer-based language models, data curation, and optimization for deployment. Collaborate on research implementation and evaluation for Small Language Models (SLMs).
What Youll Do:
- Fine-tune transformer-based language models using Python and PyTorch
- Perform training data curation, cleaning, and synthetic data generation
- Design and implement task-specific evaluation and benchmarking frameworks
- Optimize model serving and inference using frameworks such as vLLM, TGI, Ollama, llama.cpp, or TensorRT-LLM
- Deploy models across GPU, CPU, and edge environments
- Read and implement recent ML research into experiments
What We re Looking For (Must-Haves):
- Hands-on experience fine-tuning transformer-based language models
- Strong Python and PyTorch skills
- Deep experience with Hugging Face libraries (Transformers, PEFT, Datasets, Accelerate, TRL)
- Experience with SFT using LoRA/QLoRA and understanding of CPT, DPO, and GRPO
- Ability to curate and generate synthetic training data
- Experience designing evaluation and benchmarking frameworks
- Knowledge of model distillation, pruning, and quantization
- Experience with model serving and inference optimization frameworks
- Experience with deployment on GPU, CPU, and edge devices
- Ability to read and implement recent ML research papers
Good to Have (Optional - only if mentioned):
- Experience with continued pre-training, distributed training, structured generation, RL for LLMs, and knowledge distillation
Qualifications:
As per requirement
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Location: Bangalore, Pune, Gurgaon ( Hybrid)
Experience: 4+ years
About BinQle
BinQle is a global delivery and execution partner supporting enterprises across the US, India, Singapore and Australia. We specialize in structured hiring, managed teams, and long-term delivery support.
Role Summary:
Responsible for fine-tuning transformer-based language models, data curation, and optimization for deployment. Collaborate on research implementation and evaluation for Small Language Models (SLMs).
What Youll Do:
- Fine-tune transformer-based language models using Python and PyTorch
- Perform training data curation, cleaning, and synthetic data generation
- Design and implement task-specific evaluation and benchmarking frameworks
- Optimize model serving and inference using frameworks such as vLLM, TGI, Ollama, llama.cpp, or TensorRT-LLM
- Deploy models across GPU, CPU, and edge environments
- Read and implement recent ML research into experiments
What We re Looking For (Must-Haves):
- Hands-on experience fine-tuning transformer-based language models
- Strong Python and PyTorch skills
- Deep experience with Hugging Face libraries (Transformers, PEFT, Datasets, Accelerate, TRL)
- Experience with SFT using LoRA/QLoRA and understanding of CPT, DPO, and GRPO
- Ability to curate and generate synthetic training data
- Experience designing evaluation and benchmarking frameworks
- Knowledge of model distillation, pruning, and quantization
- Experience with model serving and inference optimization frameworks
- Experience with deployment on GPU, CPU, and edge devices
- Ability to read and implement recent ML research papers
Good to Have (Optional - only if mentioned):
- Experience with continued pre-training, distributed training, structured generation, RL for LLMs, and knowledge distillation
Qualifications:
As per requirement
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
DistillationLlamalanguage modelsglobal deliveryLoraHugging Face TransformersLarge Language Models (LLMs)PytorchdeploymentPythonResearchMachine Learning