Amazon
Machine Learning Engineer , Commercial Software Services
Amazon, Santa Clara, California, us, 95053
Machine Learning Engineer, Commercial Software Services
AWS Foundational Data Services (FDS) Santa Clara team is responsible for enabling customers to run their critical workloads in the cloud. The FDS Santa Clara team delivers high-performance applications and solutions for customers, helping them modernize applications they run on AWS and achieve cost savings, security, scalability, and resiliency. The team also provides customers the ability to modernize their applications via refactoring, replatforming, and rehosting techniques. We are seeking a ML Engineer to experiment with ML algorithms and tools, select appropriate datasets and data representation methods, perform feature engineering, model selection and validation, run machine learning tests and benchmarking, perform fine-tuning using test results, train and retrain systems, and build prototypes. The ML focused SDE should understand deploying ML models to production, building components in a service, consider multiple design approaches, and make appropriate trade-offs for data and model parallelism at scale. The ML focused SDE should sufficiently be able to actively participate in technical and customer discussions within the team, such as participating in code reviews, design discussions, operational reviews, and working backwards exercises with customers, peers, and stakeholders.Key Job Responsibilities:You demonstrate independence in ML model development applying a range of ML tools and algorithms.You demonstrate your ability to solve difficult problems that contain visible risks or roadblocks. You have solved problems without immediately obvious solutions, though the solution may appear obvious in hindsight.You have demonstrated your proficiency with the major lifecycle of software and ML model development including design, coding, model experimentation, tuning, and model validation.You collaborate with data scientists and engineers in providing data engineering support and integrate with managed ML services. You are also capable of deploying ML models to an integration or production environment.You are active in review processes on your team (e.g., code reviews), providing meaningful feedback to others, including more senior engineers. You seek feedback on your own work actively and early enough to be actionable.You make improvements to your team’s development and experimentation processes.You communicate effectively to your team about the work you deliver.You mentor new teammates and/or interns to help them become productive contributors.Minimum Requirements:3+ years of non-internship professional software development experience.2+ years of non-internship design or architecture (design patterns, reliability, and scaling) of new and existing systems experience.Experience programming with at least one software programming language.3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.Bachelor's degree in computer science or equivalent.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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AWS Foundational Data Services (FDS) Santa Clara team is responsible for enabling customers to run their critical workloads in the cloud. The FDS Santa Clara team delivers high-performance applications and solutions for customers, helping them modernize applications they run on AWS and achieve cost savings, security, scalability, and resiliency. The team also provides customers the ability to modernize their applications via refactoring, replatforming, and rehosting techniques. We are seeking a ML Engineer to experiment with ML algorithms and tools, select appropriate datasets and data representation methods, perform feature engineering, model selection and validation, run machine learning tests and benchmarking, perform fine-tuning using test results, train and retrain systems, and build prototypes. The ML focused SDE should understand deploying ML models to production, building components in a service, consider multiple design approaches, and make appropriate trade-offs for data and model parallelism at scale. The ML focused SDE should sufficiently be able to actively participate in technical and customer discussions within the team, such as participating in code reviews, design discussions, operational reviews, and working backwards exercises with customers, peers, and stakeholders.Key Job Responsibilities:You demonstrate independence in ML model development applying a range of ML tools and algorithms.You demonstrate your ability to solve difficult problems that contain visible risks or roadblocks. You have solved problems without immediately obvious solutions, though the solution may appear obvious in hindsight.You have demonstrated your proficiency with the major lifecycle of software and ML model development including design, coding, model experimentation, tuning, and model validation.You collaborate with data scientists and engineers in providing data engineering support and integrate with managed ML services. You are also capable of deploying ML models to an integration or production environment.You are active in review processes on your team (e.g., code reviews), providing meaningful feedback to others, including more senior engineers. You seek feedback on your own work actively and early enough to be actionable.You make improvements to your team’s development and experimentation processes.You communicate effectively to your team about the work you deliver.You mentor new teammates and/or interns to help them become productive contributors.Minimum Requirements:3+ years of non-internship professional software development experience.2+ years of non-internship design or architecture (design patterns, reliability, and scaling) of new and existing systems experience.Experience programming with at least one software programming language.3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.Bachelor's degree in computer science or equivalent.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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