Machine Learning Engineer 3

About the job

Responsibilities

• Design, build, and/or deliver ML models and components that solve real-world business problems.
• Inform ML infrastructure decisions using understanding of ML modeling techniques and issues.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Collaborate as part of 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, technologies, and/or platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Leverage continuous integration and continuous deployment best practices for successful deployment of ML models and application code.
• Ensure code is well-managed for vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI.

Requirements

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