Deep Learning Researcher

IMC Trading; Sydney; Presencial; AUD 180.000 - 240.000; Jornada completa

Descripción de la vacante

IMC Trading in Sydney is seeking a Deep Learning Researcher with a proven track record of developing state-of-the-art deep learning techniques to solve complex real-world problems in quantitative trading.

You will join a team advancing deep learning research and infrastructure, including large-scale pre-training, predictive modeling and representation learning, shaping how markets are traded. This role emphasizes rigorous scientific thinking and leadership.

Formación

• PhD or Master's in CS/ML/AI or related quantitative field.
• 3+ years of deep learning research experience.
• Expertise in transformers, representation learning, self-supervised/Generative models.
• Experience training/deploying large-scale models in distributed computing.
• Strong Python skills; PyTorch/JAX/TF experience.
• Ability to communicate complex concepts clearly.
• Proven ability to thrive in a collaborative, research-driven environment.

Responsabilidades

• Build and improve advanced deep learning models to enhance trading performance across asset classes.
• Innovate in representation learning, transformers, foundation models, generative AI, RL, and related DL techniques.
• Research, prototype, and evaluate novel neural network architectures and training methodologies for market-state prediction and portfolio construction.
• Support data curation, self-supervised learning, and multimodal learning from structured and unstructured data.
• Partner with traders, researchers, and engineers to translate market insights into scalable DL solutions.
• Stay at the forefront of academic and industry developments in deep learning and share relevant research with the team.

Conocimientos

Strong communication

Collaborative

Scientific thinking

Educación

PhD or Master's in CS/ML/AI or related quantitative field

Herramientas

PyTorch

JAX

TensorFlow

Descripción del empleo

IMC is seeking a Deep Learning Researcher with a proven track record of developing and applying state-of-the-art deep learning techniques to solve complex real-world problems. This individual will join a team that is leading the advancement of deep learning research and infrastructure, including large-scale pre-training, predictive modeling and representation learning, to increasingly shape our trading.

The ideal candidate has deep expertise in modern AI and machine learning research and a passion for applying cutting-edge techniques to new domains. Prior financial industry experience is not required. We are looking for someone who can bring fresh perspectives, rigorous scientific thinking, and strong technical leadership to help build a world-class deep learning capability at IMC.

This is an opportunity to work at the intersection of AI research and quantitative trading, leading efforts spanning modern neural network architectures, self-supervised learning, foundation models, generative AI, reinforcement learning, and custom deep learning approaches designed for financial markets.

Your Core Responsibilities

• Build and improve advanced deep learning models to enhance trading performance across multiple asset classes
• Innovate in areas such as representation learning, transformers, foundation models, generative AI, reinforcement learning, and other emerging deep learning techniques
• Research, prototype, and evaluate novel neural network architectures and training methodologies applicable to market state prediction, signal generation, execution optimization, and portfolio construction
• Support large-scale data curation, feature representation, self-supervised learning, and multimodal learning from structured and unstructured datasets
• Partner with quantitative traders, researchers, and engineers to translate market insights and business objectives into scalable deep learning solutions
• Stay at the forefront of academic and industry developments in deep learning and share relevant research with the team

Your Skills And Experience

• PhD or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Engineering, or a related quantitative field
• 3+ years of experience conducting deep learning research and developing large-scale machine learning systems
• Demonstrated expertise in modern deep learning architectures, including transformers, sequence models, representation learning, self-supervised learning, and/or generative models
• Strong understanding of the theoretical foundations underlying deep learning, optimization, statistical learning, and neural network training dynamics
• Experience training and deploying large-scale models in distributed computing environments; experience with large-scale pretraining is highly valued
• Strong programming skills in Python and hands-on experience with modern deep learning frameworks such as PyTorch, JAX, TensorFlow, and associated ecosystem tools
• Experience building scalable ML infrastructure, experimentation platforms, and model deployment systems
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences
• Demonstrated ability to thrive in a highly collaborative, research-driven environment

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.