Machine Learning Engineer – LLM Evaluation & Automation
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.
Essential functions
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.
Qualifications
5+ years of experience in ML engineering, NLP, or AI/ML automation.
Advanced degree (MS/PhD) in Statistics, Data Science, Computational Social Science, Quantitative Psychology, or a related field.
Hands-on experience in prompt engineering and designing LLM-based evaluation systems is preferred
Strong understanding of machine learning principles with 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
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.
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All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.