6 jobs for "Machine Learning Engineer Graduate (Audio Understanding) - 2027 Start (PhD)"

Machine Learning Engineer Graduate (TikTok - Data - Search - Search Quality) - 2027 Start

At TikTok - San Jose

Posted on Oct 16

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Neural Graphics and World Models Research Scientist/Software Engineer Graduate (TikTok, Engine&Tools) - 2027 Start (PhD)

At TikTok - San Jose

Posted on Nov 2

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Research Scientist/Software Engineer, Neural Graphics and World Models - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

At TikTok - San Jose

Posted on Nov 2

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Machine Learning Engineer, Apple Search & Knowledge Platforms

At Apple - Santa Clara

Posted on Oct 17

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Machine Learning Engineer Manager -

At Apple

Posted on Oct 14

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Machine Learning Engineer, Apple Search & Knowledge Platforms

At Apple - Santa Clara

Posted on Oct 17

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Apple

Machine Learning Engineer Manager -

SingaporePosted 26 days ago

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Why you should apply for a job to Apple:

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65% would recommend this company to other women
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Apple's Strategic Data Solutions (SDS) team is looking for a talented manager who is passionate about leading a team of data scientists that craft, implement, and operate analytical solutions with direct and measurable impact to Apple and its customers.

You will build and lead a team of SDS machine learning engineers, who employ machine learning, statistical analysis techniques, and system design to build end-to-end solutions for Apple's fulfilment and financial programs. You will engage with a large and talented cross-functional team as we work to build out our solutions, projects and programs.

Apple's dedication to customer privacy, the adversarial nature of trader and risk, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, you will push the limits of integrating existing data science methods with engineering and business process to deliver tangible business value!

This position is based in Singapore.

Description
Lead and mentor a team of software developers and machine learning engineers
Design and maintain real-time automated decisioning systems and operations for fulfilment and financial products.
Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.
Engage with business partners and understand their unique requirements and design them technical solutions
Review the teams production code and logic for highly integrated system.
Distill and clearly communicate complex technical topics for both business and engineering stakeholders
Analyze data and tell meaningful stories to assist business partners.
Collaborate with and support the team to innovate, encouraging experimentation and growth.

Preferred Qualifications
Experience in the following a plus: operations, fulfilment, supply chain, trader, payments, financial risk

Minimum Qualifications
Graduate degree in a quantitative field or equivalent professional experience.
Experience leading a team of machine learning engineers and software engineers.
Practical experience training, deploying, and maintaining decisioning algorithms.
Familiarity with distributed databases, data warehousing, and SQL.
Ability to implement custom real-time or batch machine learning applications with their appropriate data pipelines.
Ability to comprehend and debug complex system integrations spanning toolchains and teams.
Ability to extract meaningful business insights from data and identify the stories behind the patterns.
Ability to think at a systems level to anticipate technical, business, and customer impact.
Clear communication and presentation skills.
Unwavering ability to maintain poise and a positive attitude in a challenging and dynamic environment.
Strong organizational skills with an ability to oversee and drive multiple activities at once.
Excellent problem solving skills, business acumen, and solution design mentality.
Experience writing, reviewing, and deploying production software.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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