苹果AIML - Sr. Machine Learning Engineer - Data and ML Innovation

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline—from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING: Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions.

Technical Development & Architecture * Design and implement scalable AI/ML solutions for Compliance use cases * Lead the development of efficient ML models and end‑to‑end data processing pipelines from ingestion to serving. * Build robust, production-grade AI services using Python and modern ML frameworks. * Make and document sound architectural decisions, ensuring systems are scalable, secure, and cost‑effective. * Establish and maintain high engineering standards, including testing, monitoring, and documentation. Engineering Leadership * Partner closely with data scientists, product managers, and operations teams to deliver end‑to‑end AI/ML solutions. * Define and evolve the technical architecture for AI-powered features and platforms. * Lead code reviews, enforce best practices, and elevate engineering quality across the team. * Continuously improve AI system performance, reliability, and latency through experimentation and optimization. Technical Collaboration & Operations * Work with cross‑functional partners to understand requirements, refine scope, and prioritize technical work. * Provide technical guidance and mentorship to junior and mid‑level engineers. * Collaborate with platform and DevOps teams to ensure smooth deployment, monitoring, and maintenance of AI systems. * Implement and evolve ML Ops practices (e.g., CI/CD for models, feature stores, model monitoring, and retraining workflows).

The Role We are seeking a highly motivated and skilled Full Stack Developer to join Tesla. The ideal candidate will have a strong foundation in full stack development, coupled with hands-on experience in building and deploying LLM (Large Language Model) Agents and a deep understanding of Machine Learning pipelines. Responsibilities • Design, develop and maintain scalable and efficient full stack applications especially for business intelligence (BI) reporting tool via Apache Superset, EChart or Dash. • Develop intuitive and performant user interfaces using React or Next.js. • Build and manage backend services using Python (FastAPI or Flask), with flexibility for Java (SpringBoot) . • Build, deploy and optimize LLM application like Agentic RAG for real-world use cases. • Design and implement containerized applications using Docker and orchestrate them with Kubernetes. • Integrate and optimize data analytical solution with Neo4j and MongoDB and Apache Airflow. • Collaborate with cross-functional teams to deliver high-quality software solutions.

The Role We are seeking a highly motivated and skilled Full Stack Developer to join Tesla. The ideal candidate will have a strong foundation in full stack development, coupled with hands-on experience in building and deploying LLM (Large Language Model) Agents and a deep understanding of Machine Learning pipelines. Responsibilities • Design, develop and maintain scalable and efficient full stack applications especially for MLOps Platforms and LLM Agents. • Develop intuitive and performant user interfaces using React or Next.js. • Build and manage backend services using Python (FastAPI or Flask), with flexibility for Golang (Gin). • Build, deploy and optimize LLM application like Agentic RAG for real-world use cases. • Design and implement containerized applications using Docker and orchestrate them with Kubernetes. • Collaborate with cross-functional teams to deliver high-quality software solutions.