Machine Learning Engineer

Do you thrive on taking complex ML models out of notebooks and building production-grade systems that run at scale?

Are you looking for a high-impact, autonomous role where you directly own core subsystems end-to-end?

Great, then please read on as we have a role for you.

Our clients mission is to fundamentally change the productivity landscape around email, calendars and note taking by developing proactive, AI-native applications designed for the general public. We are bringing seamless intelligence to workflows, scheduling, and daily errands, all without requiring users to master complex prompting.

Our clients engineering culture is focused on delivering high reliability for long-running workflows, maintaining persistent context, and executing real-world tasks flawlessly. By anchoring their products in practical utility and robust architecture, they are successfully minimizing model hallucinations. Ultimately, the goal is to automate personal organization so people can focus their energy on what truly matters., * Design and build the core machine learning systems driving a proactive, forward-looking AI platform.

• Take complete end-to-end ownership of your projects, from data curation and model training to evaluation, inference, and continuous iteration.
• Translate cutting-edge research concepts into robust, highly reliable systems ready for production environments.
• Leverage live production signals and data to troubleshoot complex model anomalies and system bottlenecks.
• Drive a fast-paced development loop-deploy systems, analyze real-world performance metrics, refine approaches, and repeat swiftly.
• Partner seamlessly with research, engineering, and product teams to ensure technical milestones translate directly into tangible user value.
• Provide hands-on mentorship to fellow engineers, conduct rigorous reviews, and set a high standard for technical judgment through your own execution.
• Optimize model architectures to strictly balance latency, computational cost, system reliability, and safety at massive scale.

• Minimum of 5 years experience in a Machine Learning role
• Experience with Python, PyTorch / JAX, GPU-based training and inference systems
• Demonstrated experience building, deploying, and maintaining machine learning systems actively used in real-world environments.
• Strong practical understanding of how modern ML models behave and fail in live production, alongside the ability to effectively mitigate edge cases.
• Track record of writing clean, robust, production-grade code with an architectural mindset that goes far beyond simple scripting.
• High degree of self-direction and initiative, with a proven ability to independently drive complex technical initiatives from concept to launch.
• Ability to absorb new concepts rapidly, communicate technical trade-offs clearly, and continuously improve code and systems through iterative feedback loops.

Reasons to join:

• Small founding team, building a greenfield AI email product from scratch.
• High-caliber engineers from top tech companies; very high technical bar.
• Fully remote, global team, strong ownership, and visible impact.
• Very strong reward culture (including significant equity and high comp flexibility