Machine Learning Manager (Deep Learning)

We are seeking an experienced Machine Learning Manager to lead the development and deployment of advanced deep learning systems within a highly performance-driven environment. This role combines technical leadership, hands-on model development, and team management, working at the intersection of machine learning research, large-scale inference, and real-world production systems.

You will lead a team of machine learning engineers and researchers responsible for designing, training, optimizing, and deploying state-of-the-art models that support critical business decisions. While experience in financial markets or trading is beneficial, it is not required. We are interested in exceptional machine learning leaders from any industry who have built and scaled sophisticated deep learning systems.

Responsibilities

• Lead, mentor, and grow a team of machine learning engineers and researchers.
• Define the technical vision and roadmap for machine learning initiatives across the organization.
• Drive the end-to-end lifecycle of machine learning systems, from research and experimentation through to production deployment and monitoring.
• Partner closely with software engineers, quantitative researchers, and business stakeholders to identify opportunities where machine learning can create competitive advantage.
• Oversee the design, training, evaluation, and optimization of deep learning models for large-scale production environments.
• Establish best practices for model development, experimentation, reproducibility, deployment, and performance measurement.
• Stay at the forefront of advances in deep learning, foundation models, representation learning, reinforcement learning, and large-scale inference systems.

Required Experience

• Proven experience leading and managing high-performing machine learning teams.
• Deep expertise in machine learning and modern deep learning techniques, including neural networks, transformers, sequence modelling, representation learning, and generative AI.
• Expert-level proficiency with PyTorch and its ecosystem.
• Strong experience developing, training, and deploying machine learning models into production.
• Experience optimizing large-scale inference systems with a focus on latency, throughput, reliability, and scalability.
• Strong understanding of distributed training, GPU acceleration, model parallelism, and performance optimization.
• Excellent software engineering skills with Python and experience working in production environments.
• Strong communication and stakeholder management skills, with the ability to translate complex technical concepts into business outcomes.

Preferred Experience

• Experience working with large language models (LLMs), foundation models, or reinforcement learning systems.
• Knowledge of model compression, quantization, distillation, and inference acceleration techniques.
• Experience building ML infrastructure, MLOps platforms, and automated training pipelines.
• Familiarity with C , CUDA, Triton, Ray, Kubernetes, or similar high-performance technologies.
• Experience operating in low-latency, real-time, or high-performance computing environments.
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Mathematics, Physics, Engineering, or a related discipline.

What We're Looking For

This role is ideal for someone who combines strong people leadership with deep technical expertise. You should be equally comfortable setting strategic direction, reviewing cutting-edge research, mentoring engineers, and contributing hands-on when needed. We are looking for someone who can build exceptional teams, drive innovation, and deliver machine learning systems that operate at the highest levels of performance and reliability.