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Tech Stack
Tools & technologiesDockerPythonPyTorch
About the role
Key responsibilities & impact- Work on Sophea AI across LLM pre-training, training from scratch, fine-tuning, evaluation, and continuous model improvement
- Build production-grade ML pipelines for inference, serving, deployment, monitoring, and model lifecycle management
- Optimize model performance in production, including latency, throughput, cost efficiency, quantization, and GPU workload usage
- Work with datasets, experiments, benchmarks, and evaluation methods to improve language model quality and domain-specific performance
Requirements
What you’ll need- Strong hands-on experience with LLMs, including pre-training, training from scratch, fine-tuning, evaluation, and performance improvement
- Strong ML engineering background, including Python, PyTorch, Docker, and production ML practices
- Experience with model serving, inference optimization, quantization, GPU workloads, and frameworks such as vLLM, SGLang, NVIDIA Triton, TensorRT, TGI, or similar tools
- Ability to build production-grade ML systems, not only research prototypes, scripts, basic RAG applications, or high-level AI integrations
- Native-level Polish language proficiency
Benefits
Comp & perks- Compensation: competitive package aligned with talent benchmarks
- Impact: hands-on role working on Sophea AI, one of the most ambitious Greek-focused AI products in the market
- Work format: remote work option, with relocation support available for candidates open to working from our Athens office
- AI-native environment: real challenges across LLMs, training, fine-tuning, inference optimization, GPU workloads, and production AI systems
- NVIDIA ecosystem: access to related conferences, certifications, internal knowledge sharing, and advanced AI infrastructure through Kiefer’s strategic collaboration
- Culture: engineering-first, high autonomy, low bureaucracy, and space to build meaningful AI products
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
LLMspre-trainingfine-tuningevaluationperformance improvementML engineeringPythonPyTorchinference optimizationquantization
Soft Skills
ability to build production-grade ML systems
