Lead Machine Learning Engineer

Globalization Partners • Boston, MA

55d

About The Position

Our leading SaaS-based Global Employment Platform™ enables clients to expand into over 180 countries quickly and efficiently, without the complexities of establishing local entities. At G-P, we're dedicated to breaking down barriers to global business and creating opportunities for everyone, everywhere. Our diverse, remote-first teams are essential to our success. We empower our Dream Team members with flexibility and resources, fostering an environment where innovation thrives and every contribution is valued and celebrated. The work you do here will positively impact lives around the world. We stand by our promise: Opportunity Made Possible. In addition to competitive compensation and benefits, we invite you to join us in expanding your skills and helping to reshape the future of work. At G-P, we assist organizations in building exceptional global teams in days, not months—streamlining the hiring, onboarding, and management process to unlock growth potential for all. G-P helps organizations build global teams in minutes, not months. As part of this mission, we've created an indispensable AI agent for HR leaders, G-P Gia™ . Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over a decade of global employment and legal expertise and 100,000+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.

Requirements

• Master's degree or PhD in Computer Science, Computer Engineering, or a related technical field, with 5+ years of relevant experience in software engineering, machine learning, and MLOps.
• Highly proficient in languages like Python, Go, SQL, and Java.
• Extensive hands-on experience leveraging cloud infrastructure to build, deploy, and operationalize AI models, including deep expertise in containerization, orchestration, and managing scalable ML pipelines.
• Strong background in LLM retraining, fine-tuning, and evaluation techniques.
• Deep understanding of ML domains including NLP, LLMs, and reinforcement learning.
• Comfortable working in Agile development environments and collaborating across global teams.
• Experience communicating complex technical topics in a clear, precise, and actionable manner to stakeholders.
• Excellent technical leadership skills with deep expertise in ML infrastructure and ML engineering best practices.
• Proven track record of mentoring juniors and influencing cross-team decision-making effectively.
• Strong product sense with demonstrated ability to translate complex business requirements into practical, impactful ML solutions.
• Resourcefulness with a startup mentality and openness to dealing with unknown unknowns and wearing many hats.

Nice To Haves

• Prior experience with NLP and LLMs for legal and HR compliance applications is preferred.

Responsibilities

• Develop highly performant ML infrastructure for data and feature engineering, LLM training, evaluation, and deployment.
• Architect and manage cloud-native solutions for training and serving LLMs at scale on platforms like AWS and GCP with a strong focus on MLOps best practices to streamline and automate the ML lifecycle.
• Create evaluation frameworks and systems to monitor LLMs in production for drifts in alignment, data, and performance.
• Manage and optimize compute cost and resources across different services and platforms for large scale LLM training and deployment initiatives.
• Integrate Human-in-the-Loop (HITL) workflows and offline labeling into training and evaluation pipelines.
• Effectively communicate results, insights, and recommendations to cross-functional teams and stakeholders.
• Provide technical leadership and support developing roadmaps and coordinate efforts across teams.
• Champion best practices and engineering patterns across teams to build and maintain a robust AI platform.
• Stay up to date with the latest research in ML and related fields to evaluate and integrate technologies that enhance our platform capabilities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees