Senior Machine Learning Engineer - LLM Systems & Evaluation

Grid Dynamics; Zug; Vor Ort; CHF 140.000 - 200.000; Vollzeit

Benefits dieser Stelle

Bleeding-edge projects

Motivated team

Competitive salary

Flexible schedule

Medical insurance

Sports

Corporate events

Professional development

Zusammenfassung

Grid Dynamics in Switzerland is seeking an exceptional Machine Learning Engineer to shape the next generation of AI systems, with a focus on modern LLM architectures, RAG implementations, autonomous agents and AI safety.

Working hours require overlap until 3 pm US EST. You will own ML projects from problem definition through implementation and collaborate with product, engineering, and research teams to translate business goals into measurable ML objectives.

Qualifikationen

• Strong Python programming and 5+ years in ML engineering.
• Experience with modern ML frameworks (PyTorch, TensorFlow, JAX).
• Experience training/fine-tuning ML models and working with LLMs.

Aufgaben

• Own ML projects from problem definition through implementation.
• Design evaluation methodologies for AI/ML systems.
• Create datasets, benchmarks, and metrics for model/product performance.
• Evaluate and improve LLM-based systems including RAG, agents, safety.
• Analyze model behavior, identify failure modes, and propose improvements.
• Build and maintain ML pipelines, tooling, and evaluation infra.
• Collaborate with product, engineering, and research teams to translate goals into ML objectives.
• Prototype and iterate rapidly to solve business challenges.

Kenntnisse

Python

PyTorch

TensorFlow

LLMs

RAG

MLOps

Evaluation

Datasets

Tools

PyTorch

TensorFlow

JAX

Python tooling

Jobbeschreibung

We are looking for an exceptional Machine Learning Engineer to help shape the next generation of AI systems, with a focus on modern LLM architectures, RAG implementations, autonomous agents and AI safety.

Working hours: overlap until 3 pm US EST is required.

Responsibilities

• Own machine learning projects from problem definition through implementation.
• Design and implement evaluation methodologies for AI and machine learning systems.
• Create datasets, benchmarks, and metrics to measure model and product performance.
• Evaluate and improve LLM-based systems, including RAG applications, agents, safety systems, and end-to-end AI products.
• Analyze model behavior, identify failure modes, and recommend practical improvements.
• Build and maintain ML pipelines, tooling, and evaluation infrastructure.
• Collaborate with product, engineering, and research teams to translate business goals into measurable ML objectives.
• Prototype and iterate rapidly to solve business and product challenges.

Requirements

• 5+ years of experience in Machine Learning Engineering or a related field.
• Strong Python programming skills and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience training, fine-tuning, or adapting machine learning models.
• Experience working with Large Language Models beyond simple API integration.
• Experience evaluating AI systems and translating results into actionable recommendations.
• Experience building and maintaining machine learning systems and pipelines.
• Understanding of retrieval‑augmented generation (RAG), agentic systems, and LLM safety concepts.

Nice to have

• Experience designing benchmarks, evaluation frameworks, or automated evaluation systems.
• Experience with distributed training or large‑scale model inference.

We offer

• Opportunity to work on bleeding‑edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities

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.