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Apple AI Engineer United States, Texas, Austin 975423129
Today
This role will operate in both capacities, to augment existing AI roadmap, as well as innovate and trailblazing new frontier tech projects, crafting AI experiences that reduce time to insights and catalyze decision making.AI is a team sport, and in your role, you will be key in leading and influencing teams on the translation of business problems and questions into GenAI solutions. In this role, you will:- Architect Recommendation System based on agentic frameworks- Architect repository of images to support insights based on diffusion models- Architect agentic summarization framework for scalability- Architect RAG framework for scale- Design modular APIs, SDKs, and microservices to integrate LLMs, retrieval-augmented generation (RAG), traditional ML models, and data pipelines.- Drive interoperability with existing ML systems (e.g., forecasting, attribution, anomaly detection) and support downstream apps like dashboards, web tools, and chat interfaces.- Partner closely with data science, engineering, and sales ops to embed context-aware intelligence in decision-making tools.- Lead technical decision-making on infrastructure components, embedding safety mechanisms (e.g., autonomy sliders, grounding checks, model monitoring).- Build scalable pipelines for multi-modal agent input, memory, and semantic routing.
- 7+ years of experience in ML, data engineering, or backend development, with recent focus on GenAI and LLMs.
- Eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment.
- Ability to lead development of AI projects from start to finish.
- Comfort with ambiguity. Ability to architect a full orchestrator and business context layer for sales.
- Proficiency in Python (FastAPI, LangChain, or similar frameworks), prompt engineering, and RESTful API design.
- Hands-on experience with LLM APIs, embeddings, vector databases, and RAG workflows.
- Solid grounding in data structures, async programming, and pipeline orchestration.
- Experience working with monitoring and observability tools (e.g., Prometheus, OpenTelemetry, Weights & Biases).
- Bias for action, curiosity, and a collaborative mindset.
- Familiarity with telemetry and evaluation frameworks for AI agents.
- Experience working with data science teams on insights generation leveraging LLMs.
- Knowledge of project management, productivity, and design tools such as Wrike and Sketch.
- Strong time management skills with the ability to collaborate across multiple teams.
- Proven experience designing scalable, cloud-native platforms (e.g., AWS, GCP, or on-prem hybrid).
- Ability to balance competing priorities, long-term projects, and ad hoc requirements.
- Ability to work in a fast-paced, dynamic, constantly evolving business environment.
- B.S Degree in Computer Science/Engineering, or equivalent work experience.
- Strong experience articulating and translating business questions into AI solutions.
- Communicate results and insights effectively to partners and senior leaders, as well as both technical and non-technical audiences.
- Experience with anomaly detection and causal inference models.
- Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior leadership.
- Proven experience working with LLMs and GenAI frameworks (LangChain, LlamaIndex, etc.).
- Familiarity with embedding, retrieval algorithms, agents, and data modeling for vector development graphs.
- Proficiency with other complementary technologies for distributed systems architecture and asynchronous messaging, agent communication, and catching like RabbitMQ, Redis, and Valkey are preferred.
- Advanced Degree (MS or Ph.D.) in Economics, Electrical Engineering, Statistics, Data Science, or a similar quantitative field is preferred.
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