What you'll do
- Design, develop, and deploy machine learning models focusing 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
Key requirements
- 4+ years' experience
- Machine Learning with focus on LLMs and NLP
- Fine-tuning pre-trained large language models
- Model optimization techniques including quantization, pruning, and distillation
- Proficiency in Hugging Face Transformers, PyTorch, TensorFlow, and Python
- Cloud deployment skills and familiarity with MLOps workflows
Benefits
- Monthly allowance for meals, private health & life insurance, tools to stay connected, access to Udemy for learning, coaching and mentorship programs, collaboration with industry-leading clients, annual discretionary bonus, and volunteering opportunities.
About the job
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
4+ 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.
How We Support Your Growth
Lunch Is On Us: Monthly allowance for your favorite meals.
Health First: Private health & life insurance for peace of mind.
Set Up For Success: The right tools to stay connected and perform your best.
Curiosity Never Retires: Access to Udemy for unlimited learning.
Career Rocket Fuel: Coaching and mentorship programs tailored to your goals.
Work With The Best: Collaborate with industry-leading clients.
Celebrate Diversity: Be part of a team that values every perspective.
Performance Pays Off: Annual discretionary bonus based on yearly contributions.
Social Responsibility: Give back through volunteering and sustainability.




