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AI-ML Tech Solutions Architect

vor 1 Monat


Zürich, Zürich, Schweiz Epam Vollzeit

About the Role

We are seeking a seasoned AI-ML Tech professional in Zurich to lead the development and deployment of machine learning models, work with large datasets, and collaborate with cross-functional teams to solve business problems.

Responsibilities

  • Develop and implement ML and NLP solutions using common ML libraries and frameworks.
  • Choose and apply various methods from statistics, machine learning, and deep learning technologies to solve business problems.
  • Model user data and behavior to serve business demands and enable future business models.
  • Work closely with data engineering teams and other cross-functional teams to develop prototypes for cross-portfolio use cases and support model deployment into the cloud-native production environment.
  • Communicate and visualize data findings and techniques to both technical and non-technical audiences.
  • Stay up-to-date with research and engineering developments, including TensorFlow, PyTorch, Scikit, and Keras.
  • Integrate relevant technologies and methodologies to maintain a modern technology landscape.

Requirements

  • 8+ years of experience in machine learning, data science, and software engineering.
  • Proficient in Python and experienced with ML toolkits like TensorFlow, PyTorch, Keras, and Scikit Learn.
  • Theoretical understanding of statistical models, such as regression and clustering, and ML algorithms, including decision trees, random forests, and neural networks.
  • Strong understanding of cloud computing and cloud AI services.
  • Experience in deploying AI/ML models in production environments.
  • Experience in data analytics, feature creation, model selection, ensemble methods, performance metrics, and visualization.
  • Experience working with large datasets and distributed computing systems.
  • Experience in fine-tuning DL models, including LLMs and SLMs.
  • Familiarity with large language models from OpenAI, such as GPT 3.5 and GPT 4.
  • Knowledge of Vector Stores and RAG pipelines.
  • Proficient with data-modelling tools.
  • Proficient with multiple ML deployment strategies, including static and dynamic.
  • Excellent knowledge of CI/CD pipelines for ML algorithms, training, and prediction pipelines.
  • Experience in translating ML-based outcomes into business-digestible insights.
  • Excellent communication skills and experience in managing stakeholders at various levels.

Our Benefits

  • EPAM Employee Stock Purchase Plan (ESPP)
  • Enhanced parental leave
  • Extended pension plan
  • Daily sickness allowance insurance
  • Employee assistance program
  • Referral program
  • Hybrid working opportunities
  • Global business travel medical and accident insurance
  • Great learning and development opportunities