Role at a glance
- Job function
-
AI & Data AI Research & Applied Science
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- New York, United States
- Work arrangement
- On-site
- Experience
- 3+ years of experience conducting deep learning research and developing large-scale machine learning systems
- Education
- PhD or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Engineering, or a...
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Role Summary
The Deep Learning Researcher develops and applies deep learning approaches for quantitative trading. The role spans research, model development, and collaboration to translate market insights and business objectives into scalable solutions.
What You'll Do
- Build and improve deep learning models to enhance trading performance across multiple asset classes.
- Research, prototype, and evaluate neural network architectures and training methods for market prediction, signal generation, execution...
- Support data curation, feature representation, self-supervised learning, and multimodal learning from structured and unstructured datasets.
- Collaborate with quantitative traders, researchers, and engineers to develop scalable deep learning solutions.
- Follow academic and industry developments in deep learning and share relevant research with the team.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires a PhD or Master's degree in a related quantitative field, 3+ years conducting deep learning research and developing large-scale machine learning systems, expertise in modern deep learning architectures and their theoretical foundations, experience training and deploying large-scale models in distributed environments, strong Python programming skills and hands-on experience with modern deep learning frameworks, experience building scalable ML infrastructure and model deployment systems, and strong communication and collaboration skills.
Required
- PhD or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Engineering, or a...
- 3+ years of experience conducting deep learning research and developing large-scale machine learning systems
- Expertise in transformers, sequence models, representation learning, self-supervised learning, and/or generative models
- Understanding of deep learning theory, optimization, statistical learning, and neural network training dynamics
- Experience training and deploying large-scale models in distributed computing environments
- Strong Python programming skills and hands-on experience with PyTorch, JAX, TensorFlow, and associated ecosystem tools
- Experience building scalable ML infrastructure, experimentation platforms, and model deployment systems
- Strong communication skills and ability to thrive in a collaborative, research-driven environment
Preferred
- Experience with large-scale pretraining is highly valued
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information.
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.
About the company
IMC Trading
Large Enterprise
IMC Trading is a global proprietary trading firm that leverages technology and quantitative research to optimize trading strategies across a variety of asset classes, including equities, commodities, and derivatives. Founded in 1989 and headquartered in Amsterdam, IMC operates with a commitment to innovation and collaboration, fostering an environment where talented professionals can thrive. The firm is dedicated to responsible trading practices and actively engages in market-making to ensure liquidity and efficiency in financial markets worldwide. With a focus on continuous improvement and data-driven decision-making, IMC Trading is a leader in the fast-paced world of trading and investment.