Software Engineer

About the Role

Are you energized by applying machine learning to create meaningful impact? Do you imagine the possibilities of melding ML innovation with chip manufacturing? They're searching for a forward-thinking Machine Learning Engineer to join their Analytics Platform team and power next-gen ML services across the business.

You’ll collaborate with diverse teams—data scientists, engineers, developers, and business leads—to craft solutions that serve both internal teams and external customers. Your role will drive the design, deployment, and maintenance of ML systems that fuel intelligent decision-making within the analytics ecosystem.

What You’ll Do

• Design and implement advanced ML models to tackle complex business challenges
• Build and deploy production-ready models—whether cloud-based or on-premises—ensuring scalability, traceability, and maintainability
• Perform end-to-end model lifecycle tasks, including data prep, feature engineering, model building, evaluation, monitoring, and refinement
• Actively participate in code reviews, testing, and documentation practices that support high software quality
• Monitor model performance and take proactive steps to maintain reliability and accuracy over time
• Develop MLOps frameworks by creating infrastructure templates, CI/CD pipelines, and institutional guidelines for data science teams
• Implement containerized deployment approaches using platforms like Docker and Kubernetes
• Stay current with emerging ML technologies and integrate them into existing practices

Who You Are

• Hold a Bachelor’s or Master’s degree in Computer Science, ML, Data Science, or a related field
• Bring at least 5 years of hands-on experience in machine learning, data engineering, or related technical areas
• Well-versed with ML libraries such as TensorFlow, PyTorch, and scikit-learn
• Proficient in Python and familiar with ML lifecycle tools—from model development to CI/CD workflows
• Experienced with Microsoft Azure; knowledge of Google Cloud Platform is advantageous
• Understand data engineering, feature engineering, and model evaluation techniques within MLOps environments
• Familiarity with GDPR, ISO 27000, or other AI data governance frameworks is a plus
• Comfortable guiding junior team members and promoting service development excellence

Skills That Will Set You Apart

• A genuine passion for using ML to solve real-world challenges
• A customer-first, results-focused mindset
• Strong analytical thinking and data-driven decision-making capabilities
• Excellent communication skills and the ability to collaborate across functions
• Deep understanding of ML methods and model development best practices
• Awareness of agile development practices (e.g., Scrum)
• Solid footing in software engineering principles and practices
• Aptitude for automating workflows, ensuring efficiency and scale