ML Engineer

• Must Have Technical/Functional Skills
• 1+ years of experience building, scaling, and optimizing ML systems
• 1+ years of experience with data gathering and preparation for ML models
• 2+ years of experience developing performant, resilient, and maintainable code
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 3+ years of experience with distributed file systems or multi-node database paradigms
• 3+ years of experience building production-ready data pipelines that feed ML models.
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• Roles & Responsibilities
• Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.
• 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 that enables state-of-the-art 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, including test automation and monitoring, to ensure successful deployment of ML models and application code.
• Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
• Use programming languages like Python, Scala, or Java.
• Discretionary Annual Incentive.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.

None flagged.