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About the Role
Our client is looking for an accomplished Remote Senior Machine Learning Engineer to join their distributed engineering team. Working remotely, you'll collaborate with a global team of talented engineers and data scientists, contributing to the advancement of our AI-driven platform.
Benefits
• Highly competitive salary and stock options.
• Fully remote work arrangement with flexible hours.
• Comprehensive global health insurance.
• Generous budget for home office setup and professional development.
• Opportunity to lead challenging ML projects from concept to production.
This role is ideal for an experienced professional who excels at building and deploying sophisticated machine learning models at scale. You will lead initiatives in developing ML infrastructure, optimizing model performance, and integrating AI capabilities into core products.
This is a fantastic opportunity to make a significant impact on our AI strategy and work with cutting-edge technologies in a flexible, remote-first environment.
Key Responsibilities
• Lead the design, development, and deployment of scalable machine learning systems and pipelines.
• Optimize ML models and algorithms for production environments, focusing on performance, latency, and cost-efficiency.
• Mentor junior engineers and contribute to best practices in ML engineering and MLOps.
• Collaborate with data scientists to translate research models into robust, production-ready code.
• Develop and maintain monitoring and alerting systems for deployed ML models.
• Contribute to the architecture and infrastructure decisions for the ML platform.
Requirements
• Master's degree or PhD in Computer Science, Machine Learning, or a related field, or equivalent experience.
• 5+ years of professional experience in machine learning engineering or software development with a focus on ML.
• Expertise in Python and common ML libraries (TensorFlow, PyTorch, scikit-learn).
• Proven experience with cloud platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML).
• Strong understanding of MLOps principles and tools (e.g., Docker, Kubernetes, CI/CD).
• Excellent problem-solving skills and ability to work autonomously in a remote setting.
