Senior Frontend Engineer, AI Experience

Summary

Join our leading SaaS-based Global Employment Platform™ and help us break down barriers to global business. As a Machine Learning Engineer, you will collaborate with cross-functional teams to translate business requirements into AI-driven workflows and models. You will lead the design and development of high-performance ML pipelines, architect and manage the deployment of AI models using AWS, and create evaluation frameworks to assess LLM performance. You will also monitor production models, manage compute costs, integrate HITL workflows, and communicate results to stakeholders. This role requires technical leadership, mentoring, and a strong product sense. We offer competitive compensation and benefits, including a base salary range of $159,200 - $199,000 plus variable compensation.

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 AWS infrastructure to build, deploy, and operationalize AI models, including deep expertise in containerization, orchestration, and managing scalable ML pipelines
• Strong background in model retraining, fine-tuning, and evaluation techniques
• Deep understanding of ML domains including NLP, LLMs, and reinforcement learning
• Familiarity with data labeling tools, HITL workflows, and offline data curation strategies
• 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 system design 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 AI solutions
• Resourcefulness with a startup mentality and openness to dealing with unknown unknowns and wearing many hats

Responsibilities

• Collaborate with Product Engineers, AI Engineers, and SMEs to translate business requirements into AI-driven workflows and models
• Lead the design and development of highly performant ML pipelines for data preprocessing, feature engineering, model training, and evaluation
• Architect and manage the deployment of AI models using AWS, with a strong focus on MLOps best practices to streamline and automate the Data and ML lifecycle
• Create evaluation frameworks to assess LLM performance including hallucination frequency and response accuracy
• Monitor production models for drifts in alignment, data, and performance degradation
• Manage compute cost and resource optimization across environments for model training and deployment lifecycles
• Integrate Human-in-the-Loop (HITL) workflows and offline labeling into training 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
• Stay up to date with the latest research in ML and related fields to evaluate and integrate technologies that enhance our capabilities

Benefits

The annual gross base salary range for this position is $159,200 - $199,000 plus variable compensation