At Zoolatech, we're dedicated to transforming the business landscape with our comprehensive expertise in software development. Our collaboration with our client, a top-notch supplier of quality and compliance cloud-based software, is geared towards revolutionising the creation and distribution of life sciences products.
We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our ML team. This role requires expertise in fine-tuning, adapting, and quantizing large language models (LLMs) and creating synthetic datasets. The ideal candidate will have a strong background in machine learning, natural language processing (NLP) and computer vision (CV), and experience working with large-scale models in a production environment.
Fine-tune and adapt LLMs and multimodal models to specific tasks and domains.
Implement advanced techniques to improve model performance and accuracy.
Apply quantization techniques to optimize LLMs for efficient deployment.
Ensure model performance and accuracy are maintained post-quantization.
Develop and implement strategies for deploying quantized models in resource-constrained environments.
Design and create synthetic datasets to enhance model training and evaluation.
Implement data augmentation and generation techniques to improve model robustness.
Collaborate with data scientists and engineers to validate and refine synthetic datasets.
Collaborate with cross-functional teams to integrate adapted models into production systems.
Work closely with other machine learning engineers, data scientists, and software engineers.
Provide mentorship and guidance to junior team members.
Contribute to the development of best practices and coding standards within the team.
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or similar.
Strong understanding of NLP and CV concepts and techniques.
Experience with fine-tuning and adapting large language models (e.g., MISTRAL, BERT, T5).
Knowledge of model quantization and synthetic dataset creation tools.
5+ years of experience in machine learning engineering or a related field.
Proven track record of working with large-scale models in a production environment.
Experience in deploying machine learning models at scale.
Strong problem-solving, communication and collaboration skills
Ability to work independently, in a fast-paced, dynamic environment.
Passion for continuous learning and staying updated with the latest industry trends.
You will be a stronger candidate if you have
Experience with cloud platforms such as AWS, GCP, or Azure.
Knowledge of data engineering and ETL processes.
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
Publications or contributions to the machine learning community.