Applied AI Engineer

About A1

Over 5 billion people use fundamental applications such as email, notes, and tasks that lack built-in AI capabilities. A1's mission is to develop an intelligent proactive assistant to enhance everyday user activities like conversations, errands, organizing, and workflows with minimal input. The product emphasizes maintaining high reliability in extended workflows, persistent context retention, and real-world task execution. It must support multi-step reasoning, interact with external tools, and remain consistent despite unpredictable model outputs, aiming to reduce task completion time by approximately 90%.

Role Overview

The Applied AI Engineer position at A1 involves transforming AI model abilities into practical product behaviors. This role entails comprehensive ownership—from defining model functionalities to building the surrounding systems and ensuring dependable performance in production environments. The role converges expertise in machine learning, system design, and product development to deliver robust AI solutions that function effectively beyond demonstrations in everyday scenarios.

Key Responsibilities

• Develop and deploy AI features end-to-end, covering models, infrastructure, and user interactions.
• Design and refine prompts, tools, memory modules, and agent workflow systems.
• Convert unstructured model outputs into reliable, structured, and predictable product behaviors.
• Troubleshoot and resolve issues spanning model layers, orchestration frameworks, infrastructure, and user experience.
• Enhance performance with considerations for latency, cost efficiency, and production reliability.
• Create lightweight evaluation frameworks to assess real-world feature performance.
• Collaborate closely with product and engineering teams to transform vague problems into operational systems.

Technical Environment

• Programming language: Python
• Machine learning frameworks: PyTorch and JAX
• Large language models (LLMs) including OpenAI-style APIs, LLaMA, and Qwen
• Inference and serving infrastructure such as vLLM
• Vector databases for data management

Preferred Qualifications

• Solid grounding in machine learning principles and contemporary neural network designs.
• Experience with training, fine-tuning, or deploying machine learning models in production.
• Capability to produce high-quality, maintainable code.
• Comfort with bridging multiple layers from model architectures to infrastructure and product features.
• Excellent problem-solving aptitude within dynamic and ambiguous work conditions.
• Strong orientation towards shipping products, iteration, and continual improvement.

Expected Outcomes

• Deliver machine learning models that fulfill accuracy, latency, and reliability criteria in production.
• Rapidly identify and debug production problems and resolve underlying causes.
• Ensure robustness, reproducibility, and maintainability of data pipelines, training procedures, and inference systems.
• Work effectively across engineering, product, and research groups to launch dependable AI functionalities.
• Iterate on models and systems based on concrete real-world feedback and measurable gains.

Work Culture

A1 values small, elite teams that make collective decisions and swiftly deliver high-quality products balanced with continuous learning. The role demands autonomy, structured judgment, and responsibility to present users with an exceptional AI experience.

Interview Process

Qualified candidates will undergo three to four interviews, conducted virtually or onsite. Selection is based on evaluations by technical team members. The company prioritizes transparency and efficiency, proceeding with prompt decisions and extending offers to candidates showcasing the required skills and mindset. Joining is an opportunity to contribute to a globally impactful AI initiative.