Job VC
Data Science Engineer
Quantum is a global technology partner delivering high-end software products that address real-world problems.
We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.
Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.
We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!
About the position
Quantum is expanding its team in Central Europe and is looking for talented Data Science Engineers to join us. Our projects span multiple domains, including data analysis, fintech, computer vision, image processing, edge-device solutions, Large Language Models (LLMs), and classical Machine Learning applications. We build custom Data Science solutions for clients across various industries, combining strong engineering practices with a research-driven mindset.
Joining Quantum means becoming part of a team that values solid technical fundamentals, continuous learning, and practical problem-solving. You'll collaborate on impactful products, work with cutting-edge technologies, and contribute to projects that turn complex ideas into real-world solutions.
Must have skills:
3+ years of commercial DS/ML experience
Solid foundation in linear algebra, statistics, and probability
Strong Python, including NumPy, Pandas, and scikit-learn
Hands-on experience with PyTorch (or TensorFlow)
Deep experience in at least one of:
Computer Vision (modern DL: detection, segmentation, classification - ViT, YOLO, SAM);
LLMs / NLP (fine-tuning, RAG, prompt engineering, embeddings, evaluation);
Classical ML at scale (tabular, time series, recommender systems)
Working knowledge of Transformers and attention; familiarity with CNNs
Experience deploying models to production (Docker, REST/gRPC serving, basic monitoring)
Experience with at least one cloud platform (AWS, GCP, or Azure)
Clean code and Git workflow
Experience with SQL
Upper-Intermediate English (B2+) - you'll communicate directly with clients
Nice to have skills:
Cross-domain exposure: if your main strength is CV, some LLM exposure is a plus (and vice versa)
Edge deployment: TensorRT, OpenVINO, ONNX, quantisation, model distillation, mobile/embedded inference
LLM tooling: LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LoRA/QLoRA fine-tuning, agentic frameworks
MLOps & model monitoring: MLflow, DVC, Weights & Biases, CI/CD for ML
Classical CV with OpenCV (still relevant for hybrid pipelines and edge work)
Ability to read recent papers and implement methods in new domains
Experience working with external clients
Participation in Kaggle competitions
Your tasks will include:
Own full-cycle DS projects: scoping with the client, data prep, modelling, evaluation, deployment
Build solutions across CV, LLM/NLP, and classical ML depending on the project pipeline
Deploy models to production - cloud, edge, or hybrid, depending on client needs
Read recent research and adapt methods to client problems
Communicate technical decisions and trade-offs directly to clients
We offer:
Delivering high-end software projects that address real-world problems
Surrounding experts who are ready to move forward professionally
Professional growth plan and team leader support
Taking ownership of R&D and socially significant projects
Participation in worldwide tech conferences and competitions
Taking part in regular educational activities
Being a part of a multicultural company with a fun and lighthearted atmosphere
Working from anywhere with flexible working hours
Paid vacation and sick leave days
Join Quantum and take a step toward your data-driven future.