Machine Learning Engineer 4 (Manager, IC)

About the job

Responsibilities

• Design, build, and deliver ML models and components to solve business problems in collaboration with Product and Data Science teams.
• Inform ML infrastructure decisions based on understanding of ML modeling techniques, data, feature selection, training, and validation.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate with a cross-functional Agile team to create and enhance software for big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage CI/CD best practices, including test automation and monitoring, for successful deployment of ML models and application code.
• Ensure code is well-managed to reduce vulnerabilities, models are well-governed, and ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.

Requirements

• Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field.
• At least 4 years of experience programming with Python, Java, Golang, or C++.
• At least 4 years of Machine Learning experience using industry standard frameworks like PyTorch or Tensorflow and libraries such as Pandas, NumPy, Scikit-learn.
• At least 4 years of experience using and operating large-scale distributed systems (Spark, Ray) for AI or Machine Learning data preparation.
• At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure).
• At least 2 years of experience using Kubernetes to manage large-scale containerized Machine Learning software systems.
• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field (preferred).
• 3+ years of experience optimizing ML algorithms, configurations, and infrastructure (preferred).
• 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD (preferred).
• 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques, monitoring, and incident response plans (preferred).
• 3+ years of experience with Machine Learning techniques, model types, architectures, training concepts, and model evaluation (preferred).
• 3+ years of experience designing, implementing, and scaling production-ready data pipelines for ML models (preferred).
• 1+ years of experience as a technical lead developing ML solutions (preferred).
• Authored/co-authored a paper on an ML technique, model, or proof of concept (preferred).

Benefits

• Performance-based incentive compensation (cash bonus(es) and/or long-term incentives).
• Comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being.