Machine Learning Engineer - AWS Machine Learning Engineer - AWS …

à Sydney, Nouvelle-Galles du Sud, Australie
CDI, Plein-temps
Soyez parmi les premiers à postuler
à Sydney, Nouvelle-Galles du Sud, Australie
CDI, Plein-temps
Soyez parmi les premiers à postuler
Machine Learning Engineer - AWS
Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world!

We recently built and launched a new AWS product, Incident Manager, focused on helping our customers drive towards 100% availability of their applications and workloads. Our team works across the full stack - from highly scalable back end services, data processing systems and Machine Learning models to intuitive UX.

We are looking for a talented Machine Learning Engineer to join our team. In this role, you will partner with product managers, scientists and other engineers to prototype and develop production ready components for extracting relevant insights from various types of data streams to help customers better prepare to incidents and to mitigate issues faster. Candidates should be well familiar with best practices of training and deploying ML models in production, while being agile in developing flexible software to allow quick experimentation methods and iteration over usage patterns.

You will tackle challenging situations every day and you'll have the opportunity to work with multiple technical teams at Amazon. You will own substantial parts of the problem, with significant opportunity to affect direction and plans, removing ambiguity from the challenging problem space. Along the way, you'll join our strong development culture which includes regular tech talks, deep dive training and a passion for taking a break around a board game!

If you are passionate about building high impact software with new technologies and are eager to take on and solve challenging problems while delivering an amazing customer experience, then our team is the perfect fit for you.

• 6+ years of professional experience in a software environment, developing high quality code, including at least 3 years of professional experience developing and deploying data pipelines and ML models in production environment.
• Proficient in at least one or more object-oriented programming language: Java, Python, Go, C++ or Kotlin.
• Computer Science fundamentals in object-oriented design, data structures, algorithm design and complexity analysis.
• Knowledge of designing systems that scale through software (system architecture, security and reliability).
• Knowledge of professional software engineering best practices for the full software development life cycle; including coding standards, code reviews, source control management, build processes, testing, and operations.
• Excellent written and verbal communication skills.
• Bachelor's Degree in Computer Science or equivalent professional experience.

• Master's or PhD Degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
• 3+ years of experience with common ML techniques such as preprocessing data, training and evaluation of classification and regression models, and statistical evaluation of experimental data.
• Experience monitoring and operating data streams and ML models performance in production.
• Experience using AWS services for storing and processing data.
• Experience building data pipelines and models using different types of tabular and text data, NLP, time series, etc.
• Experience with relational SQL and NoSQL databases.
• Proficient in Python with NumPy and Pandas libraries, or equivalent.
• Proficient in Kotlin or Java.
• Experience in architecting, designing, and building complex software systems that solve ambiguous and previously undefined problems.

"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, disability, age, or other legally protected status."

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