Machine Learning Engineer

Pinnacle Talent Placement is a company focused on building scalable, cloud-native and AI-powered solutions. They are seeking a Machine Learning Engineer to lead the development of production-grade AI and machine learning platforms, collaborating closely with various stakeholders to deliver intelligent systems that enhance automation and decision-making.

Responsibilities:

• 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
• Own delivery planning, prioritization, and execution across multiple workstreams
• Identify risks and dependencies early; drive predictable, high-quality delivery
• 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

Requirements:

• Must be a legal US citizen or green card holder
• Must be in English
• Remote (EST Time Zone)
• Contract to Hire (after 6-9 months), Long Term, Full Time
• 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
• Experience with hybrid cloud environments
• Familiarity with GitHub, Atlassian Suite, and modern DevSecOps tooling
• Strong full-stack architecture and system design expertise