Machine Learning Engineer (Video Generation)
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
The computer vision engineer will work in a dynamic team as part of the Video Engineering org which develops on-device computer vision and machine perception technologies across Apples products. We balance research and product to deliver the highest quality state-of-the-art experiences innovating through the full stack and partnering with cross-functional teams to influence what brings our vision to life and into customers hands.
- M.S. or Ph.D. in Electrical/Computer Engineering Computer Science Mathematics Physics or a related field with a research focus on computer vision or data-centric machine learning.
- Production-Scale Expertise: Demonstrated success designing and shipping petabyte-scale image/video data systems to production.
- Domain Depth: Hands-on experience in at least one of the following areas: video generation pipelines multimodal LLM training or data-centric AI workflows.
- Technical Stack: Proficient in Python and C or Rust with production experience using at least one distributed data framework (e.g. Spark Ray Flink Dask).
- Communication & Collaboration: Exceptional written and verbal English skills; comfortable presenting to large technical audiences and partnering with cross-functional teams.
- Deep familiarity with video-generation and multimodal foundation models including the specialized data-loading strategies they demand.
- Proven track record curating and serving 10 PB or 1 B-item datasets for machine-learning and computer-vision workloads with an emphasis on reliability privacy and cost efficiency.
- Publications or significant OSS contributions in scalable data systems dataset retrieval/search or data-centric AIand active participation in relevant benchmarks challenges or steering committees
- Hands-on mentality to own engineering projects from inception to shipping products and the ability to work independently and as part of a cross-functional team.
- Track records of adopting ML to solve cross-disciplinary problems.
- Team-oriented self-motivated and relentlessly focused on translating ambitious ideas into measurable impact.
Key Skills
- Sales Experience
- Door-to-Door Experience
- B2B Sales
- Time Management
- Marketing
- Cold Calling
- Salesforce
- Inside Sales
- Telemarketing
- Customer relationship management
- CRM Software
- Lead Generation
About Company
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