LLM Engineer
Sydney
AI/ML
Permanent / Full Time
Are you ready to apply for one of the most exciting opportunities in the entire AI / ML Market?
This is a chance to join a newly created innovation squad in a fantastic tech product company. Brand new business unit that is tackling some of the biggest problems in AI and you have the chance to be a part of it!
Nuage has previously placed several engineers across Software, Data and DevOps into this company and have been engaged exclusively to build out this new squad.
Responsibilities:
Your Experience:
This is genuinely one of the best opportunities that I have come across in this space. Apply or reach out to jonathan@nuagetg.io to learn more!
APPLY NOW
This is a chance to join a newly created innovation squad in a fantastic tech product company. Brand new business unit that is tackling some of the biggest problems in AI and you have the chance to be a part of it!
Nuage has previously placed several engineers across Software, Data and DevOps into this company and have been engaged exclusively to build out this new squad.
Responsibilities:
- Develop, fine-tune, and optimize large language models and computer vision algorithms to meet project and business objectives.
- Design and implement scalable machine learning pipelines to handle training, validation, and deployment of LLMs and computer vision models.
- Research and integrate the latest advancements in deep learning, natural language processing, and computer vision into existing workflows.
- Build, test, and improve deep learning models for tasks such as image recognition, object detection, segmentation, and multimodal interactions.
- Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to design innovative ML solutions.
- Prepare datasets by performing tasks like data preprocessing, annotation, augmentation, and ensuring data quality.
- Monitor and evaluate model performance, identifying bottlenecks and addressing model drift using effective retraining strategies.
- Deploy machine learning models to production environments with a focus on optimizing inference time and resource usage.
- Document methodologies, experiments, and results, providing technical guidance to other team members.
- Explore and implement frameworks and tools for scaling LLMs and computer vision models on distributed systems or cloud platforms.
Your Experience:
- Strong understanding of machine learning concepts and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Hands-on experience with large language models and natural language processing techniques, such as tokenization, embeddings, or transformer-based architectures.
- Proven expertise in computer vision tasks like image classification, object detection, segmentation, and multimodal applications.
- Proficiency in programming languages like Python, C++, or Java, with a focus on developing and debugging ML algorithms.
- Experience with data preprocessing, annotation, and augmentation techniques for ML model training.
- Familiarity with model evaluation metrics and techniques for assessing performance, such as precision-recall curves, confusion matrices, or loss functions.
- Knowledge of distributed computing, cloud platforms, and tools for scaling ML models (e.g., Kubernetes, AWS, or Azure).
- Background in deploying and optimizing models in production environments, ensuring efficient inference and low latency.
- Strong problem-solving skills and experience in debugging complex ML pipelines and workflows.
This is genuinely one of the best opportunities that I have come across in this space. Apply or reach out to jonathan@nuagetg.io to learn more!
