Machine Learning Engineer, Video Search Team

Machine Learning Engineer, Video Search Team Seattle, Washington, United States Machine Learning and AI The Apple Services Engineering AI/ML organization is hiring a Machine Learning Engineer to join the Video Search team. Our team builds the core intelligence that powers search discovery experiences in the Apple TV App, Siri, and Spotlight cross platforms, helping users effortlessly find and enjoy the content they love. We are a collaborative, high‑impact team that values innovation, craftsmanship, and end‑to‑end ownership from idea to launch. Our systems combine large‑scale data, modern retrieval and ranking models, and a deep commitment to user privacy. Join us, you’ll develop scalable systems and machine learning models that drive search relevance, personalization, and understanding of content at scale. Working closely with cross‑functional partners in product and design, you’ll translate cutting‑edge research in advanced machine learning and generative AI into secure and delightful production features used by millions every day. Description As a Machine Learning Engineer on the Video Search team, within the Apple Services Engineering AI/ML organization, you will design and deploy large‑scale ML systems that power search and discovery across Apple platforms. You’ll apply machine learning, natural language understanding, and generative AI to model user intent and deliver relevant, personalized results. Your work will involve building and optimizing cutting‑edge data processing, ML models, retrieval pipelines, and ranking systems that operate at global scale and under strict privacy standards. This is a hands‑on role where you will collaborate closely with cross‑functional teams to bring advanced ML technologies into production—shaping how users discover content they love in Apple TV app, cross Apple TV partners on Apple platforms, also through Siri and Spotlight. Responsibilities Solve complex research problems and implement solutions from concept to execution. Design and implement retrieval and ranking systems using semantics and user context. Build and deploy ML, NLP and LLM models to improve search relevance and personalization. Analyze data and model performance to identify opportunities for search quality enhancement. Develop automated tests for continuous integration and ensure successful production deployment. Conduct A/B tests to measure search improvements. Collaborate with cross‑functional teams to innovate intelligent video catalog text search. Enhance search recall and ranking for global Apple devices across all platforms and languages. Utilize big data tech to evaluate content discovery features. Ensure systems meet Apple’s privacy, efficiency, and user experience standards. Minimum Qualifications 4+ years of industry or practical experience in machine learning, NLP, IR, or more recently Large Language Model (LLMs). Strong programming skills in Python, Java and Go for building scalable ML systems. Hands‑on expertise in ML libraries such as PyTorch, JAX, TensorFlow for model training and deployment. Ability to translate product goals into technical solutions, improving user experience. Strong communication, collaboration, and analytical problem‑solving skills. In‑depth knowledge of search and information retrieval fundamentals, including indexing and ranking. Experience with retrieval and ranking algorithms and building big data pipelines using Hadoop, Java, Scala, Spark and more. Industrial experience in search, classification, recommendation systems, or related fields. Familiarity with A/B testing and data‑driven product development. Passionate about creating products loved by customers at Apple. Master’s degree or higher (or equivalent practical experience) in Computer Science, Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field. Preferred Qualifications Experience with search or recommendation systems, and semantic retrieval or vector databases. Expertise in transformer architectures, embeddings, and retrieval or ranking models. Experience in applying or fine‑tuning LLMs for understanding and generation tasks. Familiarity with prompt design, context management, RAG and Agentic architectures and solutions. Exposure to evaluation and safety frameworks for LLM‑based systems. Knowledge of reinforcement learning and other modern post‑training practices for LLMs. Passion for developing intelligent, human‑centered experiences to enhance content discovery. At 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 $139,500 and $258,100, 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. Learn more about your EEO rights as an applicant. Apple accepts applications to this posting on an ongoing basis. #J-18808-Ljbffr