Applied AI Engineer

About ActAI

ActAI is on a mission to revolutionize everyday applications like email, notes, and tasks by integrating proactive AI, aimed at users unfamiliar with advanced inputs. Their product emphasizes high dependability in long-running workflows, maintaining consistent context, and accomplishing real-world tasks to minimize AI hallucinations, ultimately helping users prioritize meaningful activities.

Role Overview

The Applied AI Engineer will contribute to developing a proactive AI system that comprehends context across conversations, plans actionable steps, and progresses tasks autonomously over time. This role involves translating model capabilities into functioning product features, handling end-to-end problem solving—from modeling through system deployment to live production reliability.

Key Responsibilities

• Develop and release AI features encompassing model design, system infrastructure, and user experience integration.
• Create and refine prompt strategies, tooling, memory management, and agent workflows to improve AI performance.
• Convert unstructured model outputs into dependable and predictable behavior.
• Troubleshoot issues across modeling, orchestration, infrastructure, and user experience layers.
• Enhance system performance by optimizing latency, operating costs, and production stability.
• Build and maintain evaluation frameworks to monitor the real-world impact of AI functionalities.
• Collaborate closely with product and engineering teams to transform ambiguous challenges into practical solutions.

Technology Stack

• Python programming language
• Machine learning frameworks such as PyTorch and JAX
• Large language models including OpenAI APIs, LLaMA, and Qwen
• Inference and serving platforms like vLLM
• Vector databases for efficient data retrieval

Ideal Candidate Qualifications

• Strong understanding of machine learning principles and state-of-the-art neural network architectures
• Experience in training, fine-tuning, or deploying machine learning models in production
• Ability to produce clean, maintainable, and high-quality production code
• Comfortable working across multiple layers including models, infrastructure, and product interfaces
• Excellent problem-solving skills in dynamic and uncertain environments
• A proactive mindset focused on shipping features, iterative refinement, and continual enhancement

Expected Outcomes

• Deliver ML models in production that meet defined benchmarks for accuracy, latency, and reliability
• Rapidly identify and resolve production issues, addressing their root causes effectively
• Create robust, reproducible, and maintainable data pipelines, training workflows, and inference systems
• Maintain productive collaboration with engineering, product, and research teams for dependable ML-powered feature releases
• Drive improvements based on measurable real-world feedback and performance data

Work Culture

ActAI embraces small, elite teams that prioritize collective decision-making and rapid progress, balancing quality output with continuous learning. Team members are expected to work independently, apply sound judgment, and deliver structure amidst ambiguity to build transformative AI products for global users.

Interview Process

Applicants deemed suitable will undergo between three and four interviews conducted virtually or onsite, facilitated by technical team members. The company emphasizes transparency and prompt decisions, aiming to onboard exceptional candidates who share a passion for delivering practical AI benefits to billions worldwide.