Systems Research Engineer, Machine Learning Systems

Welcome to Workwarp: Pioneering the Future of AI At Workwarp, we're on a mission to revolutionize the world of artificial intelligence by building the next generation AI platform. As a leader in the tech industry, we're committed to innovation, excellence, and collaboration. Our team is comprised of talented individuals who share a passion for machine learning, research, and development. We're now seeking a highly skilled Systems Research Engineer, Machine Learning Systems to join our team and contribute to the development of our cutting-edge AI infrastructure. About the Position As a Systems Research Engineer specialized in Machine Learning Systems, you will play a vital role in researching and building our AI platform. You will work closely with our modeling, algorithm, and engineering teams to design large-scale distributed training systems and a low-latency/high-throughput inference engine. Your expertise will be crucial in ensuring that our AI infrastructure remains at the forefront of innovation, serving a diverse and rapidly growing user base. Your research skills will be essential in staying up-to-date with the latest advancements in machine learning systems, and you will have the opportunity to develop and integrate your own ideas into our existing software systems. Key Responsibilities: Optimize and Fine-Tune Existing Platforms: Optimize and fine-tune our existing training and inference platforms to achieve better performance and scalability, ensuring that our AI infrastructure remains efficient and effective. Collaborate with Cross-Functional Teams: Collaborate with our modeling, algorithm, and engineering teams to integrate cutting-edge research ideas into our existing software systems, promoting a culture of innovation and excellence. Develop and Integrate New Ideas: Develop your own ideas for optimizing our training and inference platforms, and push the frontier of machine learning systems research, contributing to the development of our AI infrastructure. Stay Up-to-Date with Industry Advancements: Stay up-to-date with the latest advancements in machine learning systems techniques, and apply relevant knowledge to our platform, ensuring that our AI infrastructure remains competitive and innovative. Requirements To be successful in this role, you will need to possess a strong background in machine learning systems, including distributed learning and efficient inference for large language models and diffusion models. You should also have knowledge of ML/AI applications and models, especially foundation models such as large language models and diffusion models, including how they are constructed and used. Essential Qualifications: Strong Background in Machine Learning Systems: A strong background in machine learning systems, including distributed learning and efficient inference for large language models and diffusion models. Knowledge of ML/AI Applications and Models: Knowledge of ML/AI applications and models, especially foundation models such as large language models and diffusion models, including how they are constructed and used. System Performance Profiling and Optimization Tools: Knowledge of system performance profiling and optimization tools for ML systems. Excellent Problem-Solving and Analytical Skills: Excellent problem-solving and analytical skills, with the ability to think critically and creatively. Education: A Bachelor's, Master's, or Ph. D. degree in Computer Science, Electrical Engineering, or equivalent practical experience. Preferred Qualifications: Experience with Distributed Learning: Experience with distributed learning and efficient inference for large language models and diffusion models. Knowledge of Cloud Computing: Knowledge of cloud computing platforms, including AWS, Azure, or Google Cloud. Experience with Containerization: Experience with containerization using Docker, Kubernetes, or other containerization tools. Programming Skills: Proficiency in programming languages such as Python, C++, or Java. Skills and Competencies To be successful in this role, you will need to possess a range of skills and competencies, including: Technical Skills: Machine Learning Frameworks: Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras. Programming Languages: Proficiency in programming languages such as Python, C++, or Java. Cloud Computing: Knowledge of cloud computing platforms, including AWS, Azure, or Google Cloud. Soft Skills: Communication: Excellent communication and interpersonal skills, with the ability to work effectively with cross-functional teams. Collaboration: Ability to collaborate with others, including researchers, engineers, and product managers. Time Management: Strong time management and organizational skills, with the ability to prioritize tasks and meet deadlines. Career Growth Opportunities and Learning Benefits At Workwarp, we're committed to the growth and development of our employees. As a Systems Research Engineer, Machine Learning Systems, you will have the opportunity to: Learn from Experts: Work with Experienced Researchers and Engineers: Work with experienced researchers and engineers who are leaders in their field. Stay Up-to-Date with Industry Advancements: Stay up-to-date with the latest advancements in machine learning systems, including new techniques, tools, and technologies. Develop New Skills: Develop Your Skills in Machine Learning Systems: Develop your skills in machine learning systems, including distributed learning and efficient inference for large language models and diffusion models. Expand Your Knowledge of ML/AI Applications and Models: Expand your knowledge of ML/AI applications and models, including foundation models such as large language models and diffusion models. Work Environment and Company Culture At Workwarp, we're proud of our company culture, which is built on the values of innovation, excellence, and collaboration. As a Systems Research Engineer, Machine Learning Systems, you will be part of a dynamic and supportive team that is passionate about machine learning and AI. Work Environment: Remote Work Options: We offer flexible remote work options, allowing you to work from anywhere in the world. Collaborative Team Environment: Our team is collaborative and supportive, with a focus on open communication and mutual respect. Company Culture: Innovation: We're committed to innovation, and we encourage our employees to think creatively and develop new ideas. Excellence: We strive for excellence in everything we do, from research and development to product delivery and customer support. Collaboration: We believe in the power of collaboration, and we work closely with our employees, partners, and customers to achieve our goals. Compensation, Perks, and Benefits We offer a competitive compensation package, including: Compensation: Competitive Salary: A competitive salary that reflects your skills and experience. Startup Equity: The opportunity to own a part of our company through startup equity. Perks and Benefits: Health Insurance: Comprehensive health insurance that covers you and your family. Flexible Work Arrangements: Flexible work arrangements, including remote work options and flexible hours. Professional Development Opportunities: Opportunities for professional development, including training, mentorship, and education assistance. Conclusion If you're a motivated and talented Systems Research Engineer, Machine Learning Systems, who is passionate about machine learning and AI, we encourage you to apply for this exciting opportunity. At Workwarp, we're committed to innovation, excellence, and collaboration, and we're looking for individuals who share our values and are passionate about making a difference. Don't miss this chance to join our team and contribute to the development of our cutting-edge AI infrastructure. Apply now and take the first step towards an exciting and rewarding career with Workwarp. Apply for this job