Machine Learning Engineer

Machine Learning Engineer Status: Must be a legal US citizen or green card holder Resume: Must be in English Location: Remote (EST Time Zone) Engagement: Contract to Hire (after 6-9 months), Long Term, Full Time As part of our Americas Tax Technology Group (ATTG), you will join a technology organization building scalable, cloud-native and AI-powered solutions that solve real-world business problems. Our teams partner closely with product, data, and business stakeholders to deliver intelligent systems that drive automation, analytics, and decision-making at scale. You will lead the development of production-grade AI and machine learning platforms, contributing across the full lifecycle—from data ingestion and model development to deployment, monitoring, and continuous improvement—ensuring solutions are secure, reliable, and aligned with enterprise standards. Job Description We are seeking an experienced, hands-on Engineering Manager to lead multiple teams working across AI/ML and full-stack platforms within our ecosystem. This role blends strong software engineering leadership with applied machine learning, requiring close collaboration with architecture, data, and senior leadership. You will be responsible for driving execution across complex systems, setting a high bar for engineering quality, and ensuring the successful delivery of scalable AI solutions in production. The ideal candidate brings deep technical expertise, strong ownership, and a track record of building and operating high-performing engineering teams in cloud-native environments. Key Responsibilities Team Leadership and Management: • Lead and scale 2–4 engineering teams, driving high performance, accountability, and engineering excellence • Stay close to the code and architecture, guiding design decisions and managing technical debt • Provide technical leadership and unblock teams in complex problem-solving scenarios Project and Priority Management: • Own delivery planning, prioritization, and execution across multiple workstreams • Identify risks and dependencies early; drive predictable, high-quality delivery Engineering Excellence and Operations: • Uphold engineering best practices across development, testing, and deployment • Track and report key engineering metrics and system performance • Ensure strong InfoSec posture and production readiness • Drive high-quality documentation as a core engineering deliverable Qualifications • Proven experience leading engineering teams delivering complex, distributed systems • Strong proficiency in modern full-stack development (Angular, microfrontends, C#) • Strong knowledge of React and Python, including deep learning libraries • Experience deploying and managing machine learning models on Azure, including training pipelines • Extensive experience with Azure cloud-native architectures • Strong expertise in Bicep, GitHub Actions, and infrastructure as code • Strong focus on logging, monitoring, and observability • Experience with containerization and orchestration • Deep understanding of test automation (unit, integration, e2e) • Excellent communication and stakeholder management skills Preferred Qualifications • Experience with hybrid cloud environments • Familiarity with GitHub, Atlassian Suite, and modern DevSecOps tooling • Strong full-stack architecture and system design expertise