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ML Engineer/Data Scientist


Our opportunity

ML Engineer / Data Scientist

Artificial Intelligence (AI) and data are at the core of our Group’s digital transformation. It will support us improving our product offerings, enhance customer service and underwriting capabilities. We are looking for an innovative, visionary, hands-on professional who possesses the passion and experience to take a key role within Zurich’s Group AI & Data Transformation team. Using and embedding deep learning, large language models (LLM), computer vision, machine learning and next generation agents to unlock the power of Generative AI, you will help to improve key business outcomes, through insights generation and human augmentation. You will join our multidisciplinary team that ideates, develops, implements, and deploys AI at the forefront. This is an excellent opportunity to take advantage of emerging AI trends to a real-world difference.

To do this we are looking for a hands-on, team-oriented personality with a passion for technology- and business-driven innovation and who wants to work with a team of talented AI experts, machine learning engineers, data engineers, backend developers, ML Ops professionals, architects, and AI Governance specialists.

Your role
As a ML Engineer / Data Scientist, your main responsibilities will include: 


  • Design and develop machine learning models to solve specific business problems in insurance
  • Collect, preprocess, and explore large datasets to extract meaningful insights
  • Train and fine-tune machine learning models to optimize performance
  • Develop and implement algorithms to solve complex problems
  • Collaborate with cross-functional teams to integrate machine learning solutions into products and services
  • Monitor and maintain machine learning systems to ensure optimal performance and scalability
  • Stay up-to-date with the latest research and technology advancements in the field of machine learning


Your Skills and Experience

As a ML Engineer / Data Scientist, your skills and experience will ideally include:


  • 1+ year of experience as ML engineer, Data Scientist or similar
  • Strong understanding of machine learning algorithms, large language models and statistical modeling
  • Expertise in programming languages such as Python, Java, or C++
  • Experience with machine/deep learning and NLP frameworks such as TensorFlow, PyTorch, scikit-learn, Langchain, Pinecone, others
  • Willingless to learn and adapt to emerging tools, techniques, and trends in large language models, such as Langchain or Pinecone
  • Strong track record with ML engineering techniques in cloud environment (Azure, AWS)
  • Ability to work with large datasets and distributed computing platforms such as Spark
  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration skills


We offer

Apart from monthly salary offer starting from 2 000 EUR/gross and a yearly bonus we offer benefits package which includes:


Working time benefits

Personal days off, Concentrated work week, Additional vacation, Home office, Extra days off at occasion of childbirth, Sabbatical leave, Workation


Monetary benefits

Life insurance from Zurich Austria, Compensation for salary loss during sick leave, 3rd pension pillar contribution, Risk Life Insurance, Meal contribution on top of the legally required minimum, Years of service bonus, Wedding bonus, Baby bonus


Other benefits

Edenred electronic cafeteria, Public Transport contribution, Maternity leave benefits, Company and team events, Free parking at the office building, Massages in the office



Professional Certifications, Online Education Portals, Extensive Onboarding program, Strengths based culture (GALLUP)


  • Location(s): Bratislava
  • Remote working: Yes, within Slovakia
  • Schedule: Full-time


About us

At our company, we recognize the importance of fostering an open-minded, safe and inclusive environment for everyone. We stand with diversity and respect different backgrounds and lifestyles. That's why we've implemented numerous initiatives to ensure our employees feel comfortable, accepted, and respected at all times.

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