Senior ML scientist

Company Description CarbonForge is revolutionizing AI inference with a focus on optimizing energy efficiency. With energy consumption often becoming a constraint in scaling AI systems, CarbonForge provides solutions that reduce power requirements without compromising latency or model quality. By integrating seamlessly with existing compile and deployment workflows, the company's innovative platform identifies optimal configurations to lower energy consumption while meeting key performance benchmarks. Their mission is to enable scalable, efficient AI deployments, ensuring energy does not hinder technological progress. Role Description CarbonForge is seeking a Senior Machine Learning Scientist for a full-time hybrid role based in Montreal, QC, with opportunities for remote work flexibility. In this role, you will design, develop, and optimize machine learning models and techniques specifically addressing energy efficiency challenges in AI inference. You will conduct experiments, analyze model performance, and collaborate with cross-functional teams to integrate solutions into production pipelines. Staying at the forefront of advancements in AI, you will contribute to research, develop practical applications, and support the deployment of cutting-edge algorithms for efficient inference. Qualifications • Strong background in machine learning, deep learning, and AI, including proficiency in frameworks like TensorFlow or PyTorch. • Experience with performance optimization, including working with hardware accelerators such as GPUs, TPUs, or other AI-specific hardware. • Proficient knowledge in programming languages such as Python, C++, or similar, and experience with software development best practices. • Expertise in computational efficiency, energy optimization, and profiling tools to analyze and enhance energy use in AI systems. • Familiarity with systems-level concepts such as compilers, kernel optimization, precision, and hardware-specific configurations. • Strong research skills with a proven track record of publishing in top-tier conferences or journals. • Demonstrated ability to work in a collaborative team environment while also being capable of independent research and problem-solving. • An advanced degree (Ph.D. preferred, or equivalent experience) in Computer Science, Machine Learning, Electrical Engineering, or a related field. • Experience with distributed systems or large-scale AI deployments is considered an asset. • A passion for energy efficiency in AI and commitment to innovation in sustainable computation.