Description

Design, build, and deploy ML models and infrastructure to solve complex business problems.

This role is on-site.

Responsibilities

• Design and deliver ML models, selecting appropriate algorithms, data, and features for optimal performance.
• Build and maintain optimized data pipelines and cloud-based architectures to support scalable ML applications.
• Automate testing, deployment, and monitoring using CI/CD best practices to ensure model reliability and governance.
• Collaborate with Product and Data Science teams in an Agile environment to integrate ML solutions into production software.
• Ensure code quality, model risk management, and adherence to Responsible and Explainable AI principles.

Required Skills

• 8+ years of experience designing and building data-intensive solutions using distributed computing.
• 4+ years of hands-on programming experience with Python, Scala, or Java.
• 3+ years of experience building, scaling, and optimizing ML systems in production.
• Proficiency with industry-recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
• Strong understanding of model training, hyperparameter tuning, dimensionality reduction, and bias/variance trade-offs.
• Experience with data gathering, preparation, and creating performant, resilient code.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.

Preferred Skills

• Master's or Doctoral degree in Computer Science, Electrical Engineering, Mathematics, or a similar field.
• 2+ years of experience leading teams developing ML solutions.
• Experience deploying ML solutions in public clouds (AWS, Azure, or GCP).

Key Skills

Education

Bachelor's or Master's degrees