Senior Machine Learning Engineer

Your focus will shift across these depending on where the highest-leverage work is at any given time. What you will do Design and ship production ML systems across Chakra, integrity, and evaluation domains. Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration. Build evaluation infrastructure and benchmarking pipelines that reliably measure model quality before and after deployment. Define the architecture and production bar for different signal categories from scratch. Mentor and support junior ML engineers, helping shape their technical thinking and raise the quality bar across the team. Establish ML best practices for the team: monitoring, model feedback loops, and quality standards. Who you are 4+ years building and shipping ML systems that run in production at scale. Systems thinking comes naturally. Model accuracy, data pipelines, serving infrastructure, and customer outcomes are one problem, not four. Evaluation methodology matters as much as model performance. A metric measured wrong is worse than no metric. Proficient in Python, with practical experience building data pipelines and deploying models to production. Even better if you have Experience with multimodal systems: vision, NLP, audio, or behavioral signal pipelines. LLM experience: fine-tuning, RLHF, or multi-turn agentic systems. Background in adversarial ML, fraud detection, or anomaly detection. Publications or open-source contributions in detection, robustness, or evaluation methodology. You will thrive here if Messy, undefined problems are more interesting to you than optimizing within clean ones. Ambiguity energizes you, especially when the right framing is itself part of the work. Direct access to leadership, fast feedback loops, and genuinely unsolved problems is what you are looking for. Defining what a system should be is more compelling than maintaining what already exists. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.