Senior Machine Learning Engineer

Stack

Responsibilities

• ▹Build core ML systems that power a proactive, long-horizon AI product
• ▹Own work end-to-end: data preparation, training, evaluation, inference, and iteration
• ▹Turn research ideas into working systems that run reliably in production
• ▹Debug model failures and system issues using real production signals
• ▹Iterate quickly: ship, measure outcomes, refine, and repeat
• ▹Collaborate closely with research, product, and engineering teams for real user impact
• ▹Mentor and review other ML engineers' work through example and technical judgment
• ▹Work under real production constraints: latency, cost, reliability, and safety

Requirements

• ▹Proven experience building and shipping ML systems used by real users
• ▹Understanding of how modern ML models behave — and misbehave — in production
• ▹Strong, production-quality code, thinking in systems rather than scripts
• ▹Ownership and independence, pushing work across the finish line
• ▹Fast learning, clear communication, continuous improvement through iteration
• ▹Tech stack: Python, PyTorch/JAX, GPU-based training and inference systems

Soft skills

About the company

ActAI builds proactive, AI-native applications for people who aren't used to complex prompting, aiming to bring intelligence into conversations, errands, and workflows with minimal prompting, focused on reliable long-running task completion and persistent context.