Machine Learning Engineer (Senior)

About Us Qognitive is pioneering a novel machine learning paradigm inspired by quantum mechanics and quantum cognition. Our proprietary Quantum Cognition Machine Learning (QCML) technology addresses the limitations of traditional models by emulating human cognitive processes. Designed to operate efficiently on classical hardware, QCML delivers superior performance across various applications, including finance, genomics, large language models, robotics, defense, ad tech, material science, and time series forecasting. Our approach enables data inference with a vast number of inputs, offering a versatile solution for complex, real-world challenges.

Role Summary

As a Machine Learning Performance Engineer, you will focus on optimizing and accelerating the core mathematical operations that power our machine learning models. Your primary responsibility will be improving the efficiency of dense and sparse linear algebra computations through CUDA-optimized GPU acceleration. You will focus on fine-tuning low-level numerical operations and developing high-performance computational kernels that maximize hardware utilization. You will work closely with our research and engineering teams to ensure that our custom ML architecture runs efficiently on modern GPU hardware, enabling faster training and inference.

Key Responsibilities

• GPU Optimization: Leverage CUDA to accelerate computational workflows, ensuring efficient utilization of GPU resources.
• Performance Tuning: Identify and resolve performance bottlenecks in both hardware and software components to enhance system throughput and reduce latency.
• Collaboration: Work closely with Applied Machine Learning Research Engineers and Software Engineers to integrate new models and algorithms into the existing infrastructure.
• Documentation: Maintain comprehensive documentation of system configurations, processes, and performance metrics to support continuous improvement and knowledge sharing.

Qualifications Required

• Education: Bachelor's or Master's degree in Computer Science, STEM, or a related field.

• Technical Expertise:

• Proven experience in high-performance computing environments, particularly in designing and managing infrastructure for machine learning applications.

• Proficiency in GPU programming with CUDA, including kernel development and performance optimization.

• Strong foundation in mathematics.

• Strong programming skills in languages such as C++ and Python.

• Familiarity with parallel and distributed computing paradigms.

• Problem-Solving Skills: Ability to diagnose complex system issues and implement effective solutions promptly.

• Communication: Excellent verbal and written communication skills, with the ability to convey technical concepts to diverse audiences.

• Team Collaboration: Demonstrated experience working in cross-functional teams, with a collaborative and proactive mindset.

Preferred

• Experience with Machine Learning Frameworks: Familiarity with PyTorch, JAX or similar platforms.
• Knowledge of complex linear algebra: Understanding of quantum mechanics or complex linear algebra and their application in machine learning.
• Cloud Computing: Experience with cloud platforms (e.g., AWS, GCP, Azure) and their HPC offerings.
• DevOps Practices: Knowledge of containerization (Docker), orchestration (Kubernetes), and continuous integration/continuous deployment (CI/CD) pipelines.

What We Offer

• Innovative Environment: Engage in cutting-edge projects at the intersection of quantum mechanics and machine learning.
• Professional Growth: Opportunities for continuous learning, mentorship, and career advancement.
• Collaborative Culture: Work within a diverse and inclusive team that values open communication and knowledge sharing.

How to Apply

If you are passionate about high-performance computing and eager to contribute to groundbreaking machine learning infrastructure, please submit your resume and a cover letter detailing your relevant experience and interest in the role to [email protected]. We look forward to exploring how you can contribute to our vision.

The reasonably estimated yearly salary for this role at Qognitive is: $175,000—$300,000 USD (plus Stock Options and annual performance bonus)