ML Engineer - LLM Evaluation & Automation

Grid Dynamics; United States; On-site; USD 140,000 - 170,000; Full time

Benefits offered by this job

Flexible schedule

Medical insurance

Vision and dental

Corporate social events

Professional development opportunities

Well-equipped office

Job summary

Grid Dynamics in the United States is seeking a Machine Learning Engineer specializing in LLM‑based evaluation to design and build automated systems that measure and improve the quality of model outputs.

You will lead evaluation pipelines, develop metrics, and deliver actionable insights for continuous product improvements while collaborating with cross‑functional teams across data science, engineering, and product.

Qualifications

• 5+ years of experience in ML engineering, NLP, or AI/ML automation.
• Hands‑on experience in prompt engineering and designing LLM‑based evaluation systems is preferred.
• Strong understanding of machine learning principles with a focus on NLP and advanced LLM capabilities (e.g., Chain‑of‑Thought, agentic workflows).

Responsibilities

• Design and implement automated systems and pipelines for evaluating LLM outputs.
• Develop metrics and KPIs to measure output quality, accuracy, and consistency using LLM‑based evaluations.
• Collaborate with Engineering teams to create automated logic checks and validation tools.
• Partner with Data Scientists to analyze evaluation results and optimize prompt and task structures.
• Provide feedback loops to ensure evaluation guidelines align with LLM‑based assessments.
• Investigate how LLM‑derived evaluations can enhance product reliability and user experience.
• Recommend refinements to prompt engineering, evaluation strategies, and automation tools.
• Stay informed on emerging trends in LLM evaluation, automated quality assessment, and AI toolchains.
• Continuously improve and expand automated evaluation processes based on industry best practices.

Skills

Python

SQL

Prompt engineering

LLM evaluation

NLP

Education

Bachelor’s/Master’s in Computer Science/Engineering

Tools

PySpark

Job description

We are seeking a highly skilled Machine Learning Engineer who specializes in leveraging Large Language Models (LLMs) for automated evaluation and quality assessment. In this role, you will design and build systems that automatically measure and improve the accuracy, relevance, and consistency of model outputs. You will lead initiatives to create evaluation pipelines, develop metrics, and deliver actionable insights for continuous improvements. This position requires strong technical expertise, analytical problem‑solving abilities, and the capacity to manage projects across multiple cross‑functional teams.

Responsibilities

• Design and implement automated systems and pipelines for evaluating LLM outputs.
• Develop metrics and KPIs to measure output quality, accuracy, and consistency using LLM‑based evaluations.
• Collaborate with Engineering teams to create automated logic checks and validation tools.
• Partner with Data Scientists to analyze evaluation results and optimize prompt and task structures.
• Provide feedback loops to ensure evaluation guidelines align with LLM‑based assessments.
• Investigate how LLM‑derived evaluations can enhance product reliability and user experience.
• Recommend refinements to prompt engineering, evaluation strategies, and automation tools.
• Stay informed on emerging trends in LLM evaluation, automated quality assessment, and AI toolchains.
• Continuously improve and expand automated evaluation processes based on industry best practices.

Requirements

• 5+ years of experience in ML engineering, NLP, or AI/ML automation.
• Hands‑on experience in prompt engineering and designing LLM‑based evaluation systems is preferred.
• Strong understanding of machine learning principles with a focus on NLP and advanced LLM capabilities (e.g., Chain‑of‑Thought, agentic workflows).
• Expertise in building automated evaluation or QA pipelines.
• Excellent analytical and problem‑solving skills with experience in root cause and error pattern analysis.
• Proven project management and cross‑functional collaboration experience.
• Excellent communication skills to convey complex insights to technical and non‑technical audiences.
• Detail‑oriented mindset with a focus on evaluation metrics, prompt design, and automation.
• Ability to quickly adapt to new business rules and evaluation guidelines across diverse product domains.
• Strong programming skills in Python and SQL.
• Experience with big data technologies like PySpark for data aggregation and sampling is a strong plus.
• Bachelor’s/Master’s degree in Computer Science/Engineering or a related field.

We offer

• Opportunity to work on cutting‑edge projects.
• Work with a highly motivated and dedicated team.
• Competitive salary.
• Flexible schedule.
• Benefits package – medical insurance, vision, dental, etc.
• Corporate social events.
• Professional development opportunities.
• Well‑equipped office.

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.