As an ML Edge & Cloud Engineer at SLY, you will be instrumental in developing and deploying machine learning models that power our emissions detection platform. You will work on the entire ML lifecycle, from data collection to training, validation, and optimization of classifiers. Your work will include deploying models both at the edge for real-time analysis and in the cloud for handling more complex computations.

• Design and develop machine learning models for anomalies detection, from data collection and preprocessing to model training and validation.
• Optimize and deploy classifiers on edge devices for real-time, low-latency detection.
• Develop and deploy complex machine learning models in the cloud for large-scale processing and analysis.
• Collaborate with data engineers to ensure robust data pipelines that support model training and deployment.
• Monitor and maintain deployed models, ensuring high performance and reliability.
• Continuously evaluate and improve models based on real-world performance data.
• Stay current with the latest advancements in machine learning, cloud computing, and edge AI, integrating new techniques and tools into your work.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 2-5 years of experience in machine learning and cloud computing.
• Strong proficiency in programming languages such as Python, and familiarity with ML libraries like TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, particularly in deploying and managing ML models.
• Understanding of edge computing and experience with deploying models on edge devices.

• Experience with data preprocessing, feature engineering, and building robust ML pipelines.
• Proficiency in using containerization tools like Docker and orchestration tools like Kubernetes for ML model deployment.
• Knowledge of model optimization techniques, such as quantization and pruning, for edge deployment.
• Experience in monitoring and maintaining models in production environments.
• Familiarity with DevOps practices and CI/CD pipelines for ML.
• Strong problem-solving skills and ability to work in a fast-paced, dynamic environment.

• Technical Expertise: You have a deep understanding of machine learning techniques and cloud computing, and you are passionate about applying these skills to real-world problems.
• Innovation and Curiosity: You constantly seek out new technologies and methods to improve model performance and efficiency, especially in challenging environments like the edge.
• Collaboration: You work effectively with cross-functional teams, sharing insights and integrating feedback to enhance the overall product.
• Ownership and Initiative: You take full responsibility for the models you develop, from concept to deployment, and continuously strive to optimize their performance.
• Adaptability: You are comfortable with the rapidly changing landscape of AI and cloud technologies, and you can quickly learn and apply new skills.

• Exceptionally Talented, Entrepreneurial Teams: You'll be part of small, results-driven, and autonomous teams, collaborating with some of the brightest minds in the industry.
• Unparalleled Growth Opportunities: We’re dedicated to hiring individuals with outstanding potential and providing them with the environment to excel. At SLY, even at an early stage in your career, you could be leading significant projects and making a substantial impact.
• Competitive Compensation and Equity Options: Your pay will grow quickly as your experience and impact increase. You'll also have the opportunity to receive equity options, allowing you to share in the value we create together.
• Comprehensive Benefits Package: Enjoy flexible hours, remote working options, unlimited support for learning and development, top-tier health insurance, a robust relocation package, generous parental leave, and an annual retreat to an inspiring destination. We’re committed to ensuring you have everything you need to do your best work.