gravity9

Machine Learning Engineer

• Delivery and technical leadership
• Lead the architecture and hands-on implementation of end-to-end ML systems: data ingestion, pipelines, feature stores, training, evaluation, serving, and monitoring
• Own technical decisions across the full stack, data platform, training environment, model serving, and MLOps tooling
• Set engineering standards for ML projects: experiment tracking, model versioning, reproducibility, governance, observability, drift monitoring, and CI/CD for ML
• Coach and uplift other engineers on the team in modern ML and MLOps practices
• Stay accountable for quality, security, and operational soundness of what we ship
• Pre-Sales and pipeline support
• Partner with the sales leadership team across pre-sales activity: discovery calls, scoping workshops, technical briefings, and LOE preparation
• Lead architecture and solutioning conversations with prospects and customers, translate business problems into credible, defensible technical approaches
• Provide dedicated technical support to opportunities flowing through the partners sales process, including positioning their products as part of broader data and AI architectures, joint solutioning sessions, and partner-aligned proposals
• Contribute to thought leadership and demand generation: blog posts, webinars, capability decks, conference talks, and reference architectures

Lead AI/ML, MLOps Consultant