Currently tracking 194 active AI roles, up 94% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $120k–$487k (avg $234k).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Architect - Conversational Speech Machine Learning Architect for Conversational Speech at Apple, responsible for defining modeling strategy and technical direction for speech recognition, synthesis, dialog systems, multimodal foundation models, and speech-to-speech technologies. The role involves hands-on technical leadership, translating research into production-quality systems at scale, and ensuring architectural decisions align with on-device constraints, latency, and scalability. | Post-trainAgent | 9 |
| AIML - Sr Machine Learning Engineer, Data and ML Innovation Senior Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art research in foundation models, particularly for audio data. The role involves the full ML pipeline from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning. Responsibilities include designing multi-modal data generation frameworks, building model evaluation pipelines, analyzing multi-modal data, and contributing to products with multi-modal perception data, especially audio and sensor fusion. The role also emphasizes representation learning, pre-training/fine-tuning for speech tasks, data selection techniques, and modeling data distributions. Collaboration with researchers and engineers is key, with opportunities for publishing groundbreaking research. |
| PretrainPost-train |
| 9 |
| Applied AI Engineer Applied AI Engineer at Apple Sales, focused on crafting and operating AI solutions using LLMs and agentic workflows for business problems. Responsibilities include designing agentic AI systems, translating research into production, building scalable pipelines, and leading technical decisions on infrastructure and safety mechanisms. Requires PhD or MS with significant experience in applied AI/ML, Python proficiency, and hands-on experience with LLMs, embeddings, vector databases, and agentic workflows. | AgentServe | 9 |
| Senior Machine Learning Manager, Search & Knowledge Platform Lead the E2E R&D and engineering for Generative AI models focused on summarization capabilities, including on-device and server-side LLMs, groundedness, and safety models. Develop inference frameworks and integrate with Apple's LLM infrastructure to deliver user experiences across various Apple products. | Post-trainServe | 9 |
| AIML - Applied Research Engineer, Machine Translation Applied Research Engineer focused on Machine Translation, leveraging LLMs and reinforcement learning to improve translation quality for Apple's products. The role involves end-to-end model development, from data generation and training to evaluation and production rollout, with a focus on scalability and quality. | Post-trainServe | 9 |
| Machine Learning Engineer Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team. This role involves architecting evaluation frameworks, designing MLOps pipelines for model assessment, and translating qualitative failure modes into programmatic guardrails and training signals for Foundation Models and generative AI systems. The role also involves collaborating with various teams to ensure AI experiences are reliable, safe, and aligned with human expectations. | Eval GatePost-train | 9 |
| Senior Computer Vision and Machine Learning Engineer, Creator Studio Senior Engineer to work on Generative AI for creative editing tools, focusing on computational photography and multi-modal image editing. Responsibilities include incubating ML algorithms, owning the model lifecycle (training to inference), designing data pipelines, and communicating research. Requires MS/PhD with 5+ years experience, deep ML knowledge (multimodal LLMs, MoE, PEFT, RLHF), and experience delivering customer-facing CV/GenAI products. | Post-trainServe | 9 |
| Machine Learning Systems Engineer, Siri Agent Modeling Machine Learning Systems Engineer for Siri, focusing on optimizing model training and inference for generative AI technologies on Apple Silicon. This role involves working across the ML stack, from training to deployment, to deliver production-level code for models impacting millions of users. | ServePost-train | 9 |
| Evaluation & Insights Machine Learning Engineer This role focuses on evaluating and improving AI systems by analyzing AI outputs, developing evaluation frameworks, and translating findings into actionable improvements. It involves assessing model behavior, identifying edge cases, and ensuring AI systems are reliable, safe, and aligned with human expectations. The role also involves building MLOps and automation for evaluation pipelines and collaborating with various teams to refine model performance. | Eval GatePost-train | 9 |
| Senior Engineering Manager, Applied AI & Agentic Experiences Senior Engineering Manager to lead Applied AI experiences for Channel Sales, focusing on intelligent workflows, conversational experiences, and agentic AI capabilities for the end-to-end Commerce Journey. This role involves leading a team, driving product engineering strategy, and shipping ML-powered products and features, ideally involving LLMs and AI agents. | AgentServe | 9 |
| Senior Computer Vision and Machine Learning Engineer, Creativity Apps Senior Computer Vision and Machine Learning Engineer at Apple focused on Generative AI for creative editing tools. The role involves incubating, training, evaluating, and deploying ML models, particularly diffusion models, transformers, and GANs, with a focus on computational photography and multi-modal image editing. The engineer will also work on efficient inference and collaborate with cross-functional teams to bring these technologies to Apple products. | Post-trainServe | 9 |
| Silicon Automation Engineer - Robotics and AIML Seeking an automation engineer with expertise in Silicon Validation, robotics control, AIML, and software development to build an intelligent automation system for silicon validation. The role involves integrating software and hardware, controlling robotics with computer vision and ML, and implementing AI/ML models for detection, collision avoidance, and control. | Agent | 8 |
| Senior Machine Learning Engineer, Agentic Workflows - Software Delivery Senior Machine Learning Engineer focused on building agentic workflows to improve Apple's software delivery and developer productivity. This role involves designing and implementing ML pipelines, developing intelligent systems for code analysis and search, and leading the design of generative AI solutions. | AgentServe | 8 |
| Director of Algorithms, Ads Engineering Director of Algorithms for Apple Ads, leading applied scientists and ML engineers to build and scale intelligence for ads delivery. Focuses on retrieval, ranking, auction, and budget optimization systems at massive scale, balancing research innovation with operational excellence and privacy constraints. This role involves defining strategy, roadmap, and execution for ML systems that optimize advertiser outcomes and user relevance. | ShipServe | 8 |
| AI Engineer - Wireless Systems Analysis , Wireless Technologies & Ecosystems AI Engineer role focused on developing and deploying generative AI/LLM solutions for wireless systems performance analysis. Responsibilities include architecting RAG pipelines, fine-tuning LLMs, building backend services, and establishing evaluation frameworks, with a focus on wireless log analysis and telecom-specific use cases. | AgentServe | 8 |
| Sr. Machine Learning Engineer, Siri Speech This role focuses on advancing Siri's conversational AI capabilities by designing, training, and evaluating machine learning models for production use cases. It involves building and maintaining scalable ML pipelines, optimizing models for performance, and contributing to ML infrastructure. The role requires experience across the full ML lifecycle, from data processing to deployment, with a focus on speech synthesis and recognition, natural language understanding, and dialog generation. | Post-trainServe | 8 |
| Applied Machine Learning Engineer - Developer Publications Applied Machine Learning Engineer focused on building and maintaining LLM evaluation pipelines for developer tools at Apple. The role emphasizes MLOps/LLMOps, assessing model quality, tracking regressions, and supporting continuous improvement cycles, requiring strong engineering fundamentals and LLM evaluation experience. | Eval GatePost-train | 8 |
| Staff Applied Scientist, AI Quality & Meta Evaluation Staff Applied Scientist focused on AI Quality & Meta Evaluation, responsible for designing and building the Data Quality Validation framework for LLM Judges. This role involves developing statistical and ML approaches to ensure the trustworthiness of evaluation signals, auditing LLM outputs, and establishing standards for data quality. | Eval GatePost-train | 8 |
| Applied AI Engineer - iCloud Data This role focuses on building and scaling AI-native capabilities within Apple's iCloud data platform. The engineer will design, build, and own end-to-end AI systems, including agents, retrieval mechanisms, evaluation, guardrails, and observability. Key responsibilities involve optimizing AI systems for cost and performance, exploring state-of-the-art AI techniques, and educating the broader organization on AI patterns. The role requires experience in taking LLM or agentic systems from prototype to production, proficiency in modern AI frameworks, and a strong understanding of ML/DL principles. | AgentServe | 8 |
| Staff Machine Learning Engineer, Search & Knowledge Platform Staff Machine Learning Engineer at Apple focused on Search and Knowledge Platform, developing next-generation Search and Question Answering systems using LLMs and RAG. Responsibilities include query understanding, retrieval, ranking, fine-tuning, and deploying models at scale, with a focus on production systems and online inference optimization. | ShipPost-train | 8 |
| Senior Computer Vision Machine Learning Engineer, Apple Wallet Senior Computer Vision ML Engineer at Apple, focusing on fraud and identity protection for Apple Wallet using facial recognition and adversarial object detection. The role involves applied research and production deployment of computer vision models. | Ship | 8 |
| Video Codec Machine Learning Engineer, Audio & Media Technologies The role focuses on developing next-generation video codecs by applying machine learning, deep learning, neural video compression, generative AI, and computer vision. It involves contributing algorithms to industry standards and collaborating with software and hardware teams. The role emphasizes ML-driven approaches to video coding and processing. | Post-train | 8 |
| Machine Learning Engineer, Video Search Team Machine Learning Engineer on the Video Search team at Apple, focusing on building and deploying large-scale ML systems for search and discovery across Apple platforms. The role involves applying ML, NLP, and generative AI to model user intent, optimize retrieval and ranking systems, and integrate advanced ML technologies into production features used by millions. Key responsibilities include designing and implementing retrieval/ranking systems, building/deploying LLM models, analyzing performance, and collaborating with cross-functional teams. | AgentServe | 8 |
| Senior iCloud Efficiency Engineer (GenAI & Agentic Systems) Senior Engineer to lead GenAI and agentic systems for improving efficiency in large-scale cloud infrastructure operations. Focuses on building practical AI systems for engineering workflows, capacity planning, anomaly detection, and operational safety, using LLMs, RAG, and automation frameworks. | AgentServe | 8 |
| Sr. Machine Learning Research Engineer, Siri Speech Machine Learning Research Engineer for Siri Speech team, focusing on creating and productizing ML algorithms for Speech Recognition, Speech Synthesis, and Conversational AI on Apple devices and cloud infrastructure. Requires expertise in compiled languages, ML frameworks, and applied ML, with the ability to translate research into user-facing products. | Post-trainServe | 8 |
| Engineering Manager - GenAI, AI & Data Platforms (AiDP) Engineering Manager for GenAI, AI & Data Platforms at Apple, leading a team to build scalable GenAI platform and applications, including RAG and Agentic components, with a focus on distributed systems, inference, and enterprise adoption. | AgentServe | 8 |
| Machine Learning Tools Engineer, Global Siri Machine Learning Tools Engineer for Apple's Global Siri team, focusing on building and improving LLM-powered intelligent assistant systems. The role involves end-to-end ML product engineering, from data generation and model training to deployment and evaluation, with an emphasis on scalable solutions and software engineering best practices. | ShipPost-train | 8 |
| Machine Learning Engineer Machine Learning Engineer at Apple responsible for designing, building, and deploying scalable, production-grade AI/ML systems, with a focus on LLM-powered features and AI agent workflows. This role involves end-to-end solution development, from concept to deployment, including integration into existing systems and continuous improvement of ML infrastructure. | AgentServe | 8 |
| Staff Machine Learning Engineer Staff Machine Learning Engineer at Apple focused on building and scaling ML infrastructure and generative AI platforms. The role involves developing systems for ML data, embeddings, feature workflows, and enabling GenAI applications. Key responsibilities include designing scalable systems, improving experimentation and evaluation, optimizing inference and AI Ops, and prototyping/optimizing GenAI models for production. The role emphasizes end-to-end ML workflow experience, large-scale distributed systems, and modern generative techniques. | ServeData | 8 |
| ML Engineer - Automated Evaluation and Adversarial Design ML Engineer focused on building and scaling automated evaluation systems and designing adversarial/stress-testing methodologies for AI-powered features in productivity and creative applications. The role involves assessing AI quality, particularly for multi-turn agentic experiences, and influencing model development decisions through rigorous evaluation. | Eval GateAgent | 8 |
| Applied AI Scientist This Applied AI Scientist role at Apple focuses on building and deploying scalable ML and AI solutions to enhance product intelligence and automation, particularly for creative applications like video editing. The role involves end-to-end ML pipeline development, prototyping AI features, and collaborating with engineering and product teams to bring intelligent solutions to production. It requires strong experience in statistical modeling, machine learning algorithms, large-scale data systems, and deploying models into production, with a preference for generative AI, computer vision, and LLM experience. | Ship | 8 |
| Senior Applied Scientist - AI Evaluation & Quality Systems Senior Applied Scientist focused on building and scaling AI evaluation and quality systems. The role involves developing methodologies, tooling, and autonomous QA agents to ensure the trustworthiness and quality of AI/ML systems, with a strong emphasis on human-in-the-loop evaluation and anomaly detection. Requires a blend of research and engineering skills to prototype, validate, and ship solutions. | Eval GateAgent | 8 |
| Machine Learning Engineer, Siri Speech Machine Learning Engineer on the Siri Speech team at Apple, focusing on designing, developing, and implementing ML models for speech, NLP, and multimodal applications. This role involves fine-tuning deep learning systems for speaker recognition and multimodal understanding, integrating ML solutions into production at scale, and working with large datasets to build production-quality models. The position requires strong Python skills, experience with ML algorithms and deep learning frameworks like TensorFlow/PyTorch, and knowledge of speech/audio processing. | Post-trainServe | 8 |
| Machine Learning Engineer, Siri Attention & Invocation Machine Learning Engineer for Siri's Attention & Invocation team, focusing on on-device voice invocation experiences. Responsibilities include building and deploying models, end-to-end training and evaluation pipelines, and optimizing speech/audio processing for Apple devices. Requires strong ML/DL background, speech recognition experience, and software engineering skills. | Post-trainServe | 8 |
| WW Consulting Engineer - AI/ML This role is a customer-facing AI/ML consulting engineer focused on positioning Apple's platforms and solutions within enterprise, education, and government sectors. The engineer will provide deep domain expertise on AI/ML solutions (cloud, hybrid, on-device/edge), articulate technical value propositions, advise on scalability, guide integration of AI/ML capabilities, and translate market trends into actionable guidance. The role requires extensive knowledge of Apple's AI/ML stack, including Apple Silicon, Foundation Models, Core ML, and Private Cloud Compute, as well as experience with major cloud AI/ML platforms. | ServeAgent | 8 |
| AI/ML Software Engineer - SES Gen AI Solutions, IS&T AI/ML Engineer to design, develop, and deploy intelligent solutions for modern contact center platforms, focusing on scalable AI systems for chatbots, voice assistants, speech analytics, and automated customer support workflows. The role involves building end-to-end AI pipelines, including model development, deployment, and optimization, with deep expertise in LLMs, conversational AI, and real-time inference systems. | AgentServe | 8 |
| Machine Learning Software Engineer for Location and Spatial Awareness , Sensing & Connectivity Machine Learning Software Engineer at Apple focusing on spatial awareness and applied perception technologies. The role involves architecting and implementing production software systems for new ML technologies, particularly in computer vision, foundation models, and sensor-based perception. Key responsibilities include developing perception algorithms, optimizing ML training pipelines, fine-tuning vision transformers, and integrating ML with wireless and spatial sensors for iOS devices. | Post-trainServe | 8 |
| ML Engineer, Ai & Data Platforms ML Engineer to design, build, and deploy production AI and machine learning solutions for Apple's enterprise, focusing on Generative AI and Data Platforms. The role involves working across the full ML lifecycle, building automated ML pipelines, developing LLM-based solutions (RAG, agents), and integrating ML systems with the enterprise data platform. | AgentData | 8 |
| GPU Software Architecture Engineer, Graphics, Games, & ML This role focuses on architecting and building distributed ML infrastructure for large-scale inference, specifically for powering Apple Intelligence. It involves designing parallelization strategies, optimizing the stack from low-level access to high-level algorithms, and collaborating with hardware architects. The goal is to achieve maximum hardware utilization and minimize latency for real-time user experiences, serving billions of requests daily. | ServeAgent | 8 |
| Wireless Systems AI/ML Engineer, Wireless Technologies & Ecosystems This role focuses on building next-generation AI agents and tools for analyzing wireless connectivity and performance issues in Apple products. It involves developing advanced system evaluation and debugging capabilities using AIML tools, with an emphasis on improving user experience. The role requires expertise in ML frameworks, Gen AI techniques like RAG and Agent Orchestration, and Python scripting, with a strong understanding of wireless protocols. | AgentServe | 8 |
| Video Machine Learning Engineer, Audio & Media Technologies Video Machine Learning Engineer at Apple, focusing on designing, developing, and deploying ML solutions for video processing, understanding, and enhancement. The role involves researching, prototyping, training, evaluating, and optimizing models for on-device deployment across various Apple products. It bridges deep learning research with real-world product impact. | Post-trainServe | 8 |
| Senior Machine Learning Engineering Manager, Ads Quality This role is for a Senior Machine Learning Engineering Manager for Ads Quality at Apple. The primary focus is on leading a team to build and deploy ML models that ensure the quality and integrity of the ad network, with a specific emphasis on using LLMs for relevance, safety, and trustworthiness. The role involves developing and applying advanced ML techniques in a large-scale production environment, working across product, policy, and engineering teams, and analyzing large-scale experiments. | ShipPost-train | 8 |
| Senior Machine Learning Engineering Manager – Ads Predictions This role is for a Senior Machine Learning Engineering Manager at Apple, focusing on Ads Predictions. The manager will lead a team responsible for building and scaling complex ML models for response prediction (CTR, conversion rate) under latency constraints. Key responsibilities include driving the development and deployment of state-of-the-art models, owning the full ML lifecycle from data to production serving, and championing privacy-preserving ML approaches. The role requires strong leadership, cross-functional collaboration, and hands-on experience with large-scale ML systems, including neural networks and LLM-based systems. | ServePost-train | 8 |
| Machine Learning Engineer, Computer Vision - Strategic Data Solutions Machine Learning Engineer specializing in Computer Vision for fraud detection within Apple's Strategic Data Solutions team. The role involves building end-to-end solutions, curating datasets, training models, and deploying them into a real-time platform to combat fraud, waste, and abuse. | ShipData | 8 |
| AI/Machine Learning Engineer AI/ML Engineer to build intelligent systems and deploy state-of-the-art AI models and systems across Apple's business groups. Responsibilities include implementing ML infrastructure, developing feature engineering and fine-tuning frameworks, designing ML pipelines, and optimizing models. The role requires designing systems from raw data to autonomous action, implementing RAG pipelines, working with embeddings and vector databases, building AI agents with tool use, and fine-tuning transformer models. Experience with large-scale data and ML frameworks is essential. | AgentData | 8 |
| Machine Learning Research Engineer, Generative AI Machine Learning Research Engineer focused on applying generative AI and ML to create innovative user experiences for hundreds of millions of users across Apple platforms. The role involves the full development cycle from ideation to productization, covering areas like handwriting and text recognition, synthesis, document understanding, and freeform drawing generation, with a focus on computer vision, speech recognition, deep learning, and multimodal LLMs. | ShipPost-train | 8 |
| ML Applied Scientist, Apple Services Engineering AI/ML ML Applied Scientist role focused on designing, developing, and deploying AI/ML solutions for Apple's services, including LLMs and Agentic AI, to enhance user content discovery. The role involves research, prototyping, production deployment, A/B testing, and collaboration with cross-functional teams. | ShipPost-train | 8 |
| AIML - Sr Machine Learning Engineer, Data and ML Innovation Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art ML research to complex data problems, specifically for Apple Intelligence. The role involves designing and developing a data generation and curation framework for foundation models, building evaluation pipelines, and exploring new methods for synthetic data creation across vision, text, and audio. The position also emphasizes collaboration with multidisciplinary teams and potentially publishing research. | DataPost-train | 8 |
| Senior Machine Learning Engineer (Generative AI) Senior Machine Learning Engineer focused on Generative AI, responsible for converting high-level goals into concrete requirements, implementing, evaluating, and shipping AI/ML technologies for data quality or user-facing features. Requires experience in building large-scale ML systems, generative AI models, and working with large datasets, with a strong emphasis on shipping production-ready solutions. | ShipPost-train | 8 |
| Senior Machine Learning Engineer, Search & AI Senior Machine Learning Engineer focused on developing next-generation Search and Question Answering systems using cutting-edge search technologies and large language models. The role involves improving Query Understanding, Retrieval, and Ranking, leveraging fine-tuning, reinforcement learning, embeddings, deep learning, and online learning. Experience with RAG, retrieval, and generative LLMs is crucial. | AgentServe | 8 |
