Machine Learning Engineer

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:

• 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 [email protected] to learn more!