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Key Responsibilities
- Design, build, and optimize LLM-based applications with a focus on RAG pipelines
- Develop and integrate retrieval systems (vector databases, embeddings, search engines) with generative models
- Fine-tune and evaluate large language models for specific business use cases
- Collaborate with data scientists, ML engineers, and product teams to deliver production-ready AI solutions
- Implement best practices for model deployment, monitoring, and scaling in cloud environments
- Research emerging AI techniques and apply them to improve performance, accuracy, and efficiency
- Ensure compliance with ethical AI practices, data privacy, and security standards
Requirements
- Multiple years of experience in applied AI/ML engineering
- Strong knowledge of LLMs (e.g., GPT, LLaMA, Mistral) and RAG architectures
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
- Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and search technologies
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
- Solid understanding of NLP concepts: embeddings, tokenization, semantic search
- Strong problem-solving skills and ability to work in fast-paced environments
- Excellent communication skills and collaborative mindset
Nice-to-Have Skills
- Experience with multi-modal AI (text, image, audio)
- Knowledge of MLOps practices and tools (MLflow, Kubeflow)
- Background in knowledge graphs or advanced information retrieval
- Contributions to open-source AI/ML projects
✉ Email: [email protected]
☎ Contact Number: +44(0)1915949744 (1587) / +358 753 266586
Key Skills
Ranked by relevance
ai
containerization
tensorflow
pytorch
docker
mlflow
cloud
aws
gcp
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- Posted
- Dec 18, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Helsinki
- Company
- Tenth Revolution Group
Industries
Software Development
Categories
Information Technology
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