
// Open Role at Razer
Join Razer to revolutionize gaming as a Senior Machine Learning Engineer, developing and deploying cutting-edge AI models globally for millions of users while fostering personal and professional growth.
Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
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Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.
Are you game?
- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field. - Proficiency in programming languages such as Python or R. - Experience with machine learning frameworks like TensorFlow or PyTorch. - Strong understanding of statistical analysis and data mining techniques. - Ability to preprocess and analyze large datasets. - Experience in developing and deploying machine learning models to production environment that serve millions of end users. - Familiarity with software development practices and version control systems. - Excellent problem-solving skills and attention to detail. - Strong communication and teamwork abilities. - Preferred: Experience with deep learning architectures and algorithms. - Preferred: Knowledge of big data tools and platforms. - Preferred: Familiarity with cloud services related to machine learning. - Preferred: Publications or contributions to the machine learning community. - Preferred: Proven track record of implementing, maintaining and optimizing production machine learning models.