Role Overview
We are looking for a Machine Learning Engineer for our client. In this role, you will be responsible for designing ML models, optimizing LLMs for NLP tasks, and deploying production-ready solutions across our AI platform. You will work closely with engineering and data teams to build scalable, high-performing ML capabilities.
What You’ll Be Doing
- Design, develop, and deploy machine learning models, with a focus on LLMs and NLP applications.
- Fine-tune pre-trained LLMs for domain-specific use cases.
- Implement model optimization techniques such as quantization to improve performance.
- Build and maintain ML pipelines using Hugging Face Transformers, PyTorch, or TensorFlow.
- Run experiments, evaluate model performance, and ensure robustness and reliability.
- Collaborate with software engineers to integrate ML models into MLOps and production systems.
What You’ll Bring
- 5+ years of experience in machine learning engineering or NLP-focused roles.
- Strong understanding of deep learning, LLMs, and modern NLP techniques.
- Hands-on experience fine-tuning LLMs and developing NLP models using Hugging Face Transformers.
- Strong Python skills and experience with PyTorch or TensorFlow.
- Familiarity with model optimization (quantization, pruning, distillation).
- Experience with cloud deployment (AWS, GCP, or Azure) and standard MLOps workflows.
Nice to Haves
- Experience with distributed training for large-scale models.
- Knowledge of model serving frameworks (FastAPI, TorchServe).
- Experience with Docker, Kubernetes, or large-scale ML deployments.