Apple
AIML - Sr Machine Learning Engineer, Siri Performance and Reliability
Apple, Seattle, Washington, us, 98127
AIML - Sr Machine Learning Engineer, Siri Performance and Reliability
Seattle, Washington, United States
Machine Learning and AI
The AIML Performance & Reliability team is looking for a Senior Machine Learning engineer with a proven record of building scalable statistical systems for business applications in a fast-paced environment to be the lead developer and architect on the Tools team. As a Senior ML engineer on the AIML Performance & Reliability Tools team, you will have significant influence and responsibility in improving Siri performance and user experience by building a trustworthy and explainable anomaly detection system to automatically identify regressions in Siri performance and alert engineering teams with actionable insights for debugging performance issues. You will be responsible for creating the technical vision for a trustworthy anomaly detection platform by understanding the user requirements, shortcomings of existing approaches, and identifying rigorous statistical methodology scalable for automation. If you're interested, you are someone laser-focused on iteratively delivering impact to customers with excellent statistical modeling, programming, problem solving, and communication skills, and a passion to build data tools for cross-functional customers. By building a trustworthy anomaly regression detection platform, your work will directly impact shipping high performant Siri across various platforms including iOS, VisionPro, WatchOS, etc. As a Senior ML engineer on the AIML Performance & Reliability Tools team, you will have the opportunity to make broad impact across all Apple platforms in close partnership with Engineering feature and product teams, Testing teams, and Quality teams. Your work directly improves Siri’s user experience in the hands of billions of Apple consumers.
Description
We are looking for a Senior ML Engineer who will set the technical vision for Siri’s automated anomaly detection platform for detecting performance and reliability regressions. You are someone who is passionate about shipping quality code and continually improving our anomaly detection systems. You will be responsible for defining, developing, and delivering key features for high-quality alerting to enable teams to troubleshoot regressions rapidly. You are someone who works extremely well across teams and organizations and demonstrates strong communication and technical leadership skills and the ability to engage with colleagues and leadership to find common ground on solving hard problems. You are someone who shares technical vision with leadership and engineering teams, gathers feature requirements, defines technical roadmaps, and executes efficiently. You will be responsible for technically representing the Tools team and communicating progress on key deliverables across the organization from peer groups to senior leadership. As the Senior ML engineer on the team, you will be responsible for owning the technical roadmap for the team, onboarding and mentoring team members, and leading the team to deliver high-impact outcomes. You are someone comfortable executing in a rapidly changing environment with ambiguous requirements to drive impact incrementally. You demonstrate strong problem-solving skills and are self-directed with a proven ability to execute. You continually desire learning and demonstrate attention to detail and find opportunities to innovate and share knowledge with others.
Minimum Qualifications
Graduate degree specializing in the areas of Applied Statistics, Machine Learning, Time Series Analysis, or related field
Master's degree plus at least 6 years of industry experience in statistical machine learning, or PhD degree with at least 3 years industry experience applying statistical modeling for business problems.
3 years experience building systems based on rigorous statistical or ML methodology, such as anomaly detection using time series analysis, at production scale.
3 years coding experience in programming languages such as Python, Java, or Scala
Proven record of being customer and impact-focused, ability to set the technical vision for long-term projects and delivering results iteratively
Ability to effectively communicate complex concepts and empower others to leverage self-service tools for data analysis and deep-dives
Innovative problem-solving ability with excellent analytical skills and critical thinking
Leadership experience, including being a technical lead for complex development projects demonstrating good technical judgment and prioritization skills.
Demonstrated ability to work in a complex cross-functional environment, ability to influence at all levels, and build strong relationships to deliver impact.
Key Qualifications
Preferred Qualifications
Prior experience building and owning anomaly detection frameworks for business metrics for different engineering stakeholders.
Proven record of delivering analytics tools end to end — from identifying customer requirements to quickly building prototypes to building scalable analytics tools to enable customers.
Previous experience in improving system performance and troubleshooting performance bottlenecks.
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Seattle, Washington, United States
Machine Learning and AI
The AIML Performance & Reliability team is looking for a Senior Machine Learning engineer with a proven record of building scalable statistical systems for business applications in a fast-paced environment to be the lead developer and architect on the Tools team. As a Senior ML engineer on the AIML Performance & Reliability Tools team, you will have significant influence and responsibility in improving Siri performance and user experience by building a trustworthy and explainable anomaly detection system to automatically identify regressions in Siri performance and alert engineering teams with actionable insights for debugging performance issues. You will be responsible for creating the technical vision for a trustworthy anomaly detection platform by understanding the user requirements, shortcomings of existing approaches, and identifying rigorous statistical methodology scalable for automation. If you're interested, you are someone laser-focused on iteratively delivering impact to customers with excellent statistical modeling, programming, problem solving, and communication skills, and a passion to build data tools for cross-functional customers. By building a trustworthy anomaly regression detection platform, your work will directly impact shipping high performant Siri across various platforms including iOS, VisionPro, WatchOS, etc. As a Senior ML engineer on the AIML Performance & Reliability Tools team, you will have the opportunity to make broad impact across all Apple platforms in close partnership with Engineering feature and product teams, Testing teams, and Quality teams. Your work directly improves Siri’s user experience in the hands of billions of Apple consumers.
Description
We are looking for a Senior ML Engineer who will set the technical vision for Siri’s automated anomaly detection platform for detecting performance and reliability regressions. You are someone who is passionate about shipping quality code and continually improving our anomaly detection systems. You will be responsible for defining, developing, and delivering key features for high-quality alerting to enable teams to troubleshoot regressions rapidly. You are someone who works extremely well across teams and organizations and demonstrates strong communication and technical leadership skills and the ability to engage with colleagues and leadership to find common ground on solving hard problems. You are someone who shares technical vision with leadership and engineering teams, gathers feature requirements, defines technical roadmaps, and executes efficiently. You will be responsible for technically representing the Tools team and communicating progress on key deliverables across the organization from peer groups to senior leadership. As the Senior ML engineer on the team, you will be responsible for owning the technical roadmap for the team, onboarding and mentoring team members, and leading the team to deliver high-impact outcomes. You are someone comfortable executing in a rapidly changing environment with ambiguous requirements to drive impact incrementally. You demonstrate strong problem-solving skills and are self-directed with a proven ability to execute. You continually desire learning and demonstrate attention to detail and find opportunities to innovate and share knowledge with others.
Minimum Qualifications
Graduate degree specializing in the areas of Applied Statistics, Machine Learning, Time Series Analysis, or related field
Master's degree plus at least 6 years of industry experience in statistical machine learning, or PhD degree with at least 3 years industry experience applying statistical modeling for business problems.
3 years experience building systems based on rigorous statistical or ML methodology, such as anomaly detection using time series analysis, at production scale.
3 years coding experience in programming languages such as Python, Java, or Scala
Proven record of being customer and impact-focused, ability to set the technical vision for long-term projects and delivering results iteratively
Ability to effectively communicate complex concepts and empower others to leverage self-service tools for data analysis and deep-dives
Innovative problem-solving ability with excellent analytical skills and critical thinking
Leadership experience, including being a technical lead for complex development projects demonstrating good technical judgment and prioritization skills.
Demonstrated ability to work in a complex cross-functional environment, ability to influence at all levels, and build strong relationships to deliver impact.
Key Qualifications
Preferred Qualifications
Prior experience building and owning anomaly detection frameworks for business metrics for different engineering stakeholders.
Proven record of delivering analytics tools end to end — from identifying customer requirements to quickly building prototypes to building scalable analytics tools to enable customers.
Previous experience in improving system performance and troubleshooting performance bottlenecks.
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