Machine Learning Data Scientist - Computer Vision

Apple

  • Sunnyvale, CA
  • Permanent
  • Full-time
  • 1 month ago
The Video Engineering organization is at the forefront of developing innovative technologies for future Apple products, with a strong focus on real-time video processing powered by foundation models. Our team has contributed to impactful projects such as FaceID for iOS and OpticID for Apple Vision Pro. We are currently looking for a hardworking Data Scientist to evaluate and craft Apple's machine learning based products in the field of computer vision, solutions that touch the lives of millions of users around the world. You'll be tasked to collaborate with multi-functional teams including deep learning, quality assurance, cloud infrastructure, and user research. You will drive improvements in algorithm performance and guide feature development through data driven insights, helping to deliver outstanding user experiences across Apple's product ecosystem.DescriptionVideo Engineering DAQ (Data Analytics and Quality) team is seeking a self-motivated and diligent Data Scientist to research and develop evaluation methods that support the continuous improvement of Apple's diverse computer vision projects. In this role, you will gain deep insight into Apple's algorithms and conduct in-depth failure analyses using data from on-device to large-scale user studies to uncover root causes of unexpected algorithm behavior. You will regularly and directly present your findings to Apple senior leadership and multi-functional teams, playing a key role in guiding product development. A strong programming background is essential, as you will also be responsible for building and maintaining automated pipelines that run on cluster machines to analyze and visualize data at scale.Minimum Qualifications
  • BS and a minimum of 3 years relevant experience
  • Extensive experience in data science, machine learning, computer vision and statistical data analysis
  • Proven experience in in-depth analysis of machine learning model failures
  • Proficient in crafting, conducting, analyzing, and interpreting experiments and investigations
  • Advanced programming skills in data manipulation & processing (SQL & Python preferred)
  • Expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset, AWS etc.
  • Experience presenting data to stakeholders
Preferred Qualifications
  • Familiar with machine learning interpretability methods is a huge plus
  • Outstanding verbal and written communication skills, along with strong collaborative abilities
  • Self-motivated and curious with creative and critical thinking capabilities
Pay & BenefitsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

Apple