Senior Machine Learning Engineer – LLM Systems & Evaluation
We are seeking a talented and experienced Senior Machine Learning Engineer to join our team, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, agents, and safety considerations.
The ideal candidate has a strong foundation in machine learning, practical engineering skills, and a passion for advancing AI systems in ambiguous, fast-paced environments.
About Our Client:
Our client is a global leader in technological innovation, committed to operational excellence and impactful solutions worldwide.
Essential functions
Lead end-to-end machine learning projects from problem definition to deployment
Design and implement evaluation methodologies for AI and ML systems
Develop datasets, benchmarks, and metrics to measure performance
Evaluate and optimize LLM-based systems, including RAG, agents, and safety modules
Analyze model behaviors, identify failure modes, and recommend practical improvements
Build and maintain ML pipelines, tooling, and evaluation infrastructure
Collaborate closely with product, engineering, and research teams to align ML objectives with business goals
Prototype rapidly and iterate to solve complex business and product challenges
Communicate technical findings, trade-offs, and recommendations to diverse stakeholders
Qualifications
Required:
5+ years of experience in Machine Learning Engineering or related fields
Deep understanding of machine learning fundamentals and model evaluation techniques
Strong Python skills with experience in modern ML frameworks such as PyTorch, TensorFlow, or JAX
Proven experience training, fine-tuning, or adapting large-scale models
Hands-on experience working with LLMs beyond simple API integration
Ability to evaluate AI systems and translate results into actionable insights
Experience building and maintaining ML pipelines and systems
Knowledge of RAG architectures, agentic systems, and AI safety concepts
Capable of working effectively in ambiguous problem spaces with limited data and requirements
Excellent communication skills, both written and verbal
Willingness to work up to 9 pm Swiss time
Would be a plus
Kaggle competition winners or notable programming contest achievements
ML modeling experience
Experience in designing benchmarks, evaluation frameworks, or automated evaluation systems
Experience with distributed training and large-scale inference
Building reusable ML tooling and internal platforms
Cloud platform expertise and modern MLOps practices
Experience working on user-facing AI products at scale
Research publications or experience in ML/AI research
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
- 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.Apply to the position
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Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process.
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.