Cloud AI Services Developer
Vor 5 Tagen
About the Role
We are seeking a highly skilled AI-ML Tech Engineer to join our team in Zurich. As a Machine Learning Engineer, you will develop and deploy machine learning models, work with large datasets, and collaborate with cross-functional teams to solve business problems.
Responsibilities
- Design and implement machine learning solutions using common ML libraries and frameworks.
- Choose, improve, and apply various methods from statistics, machine, and deep learning technologies to solve business problems.
- Model user data, interests, and online behavior to serve business demands and enable future business models.
- Work closely with our data engineering team and other cross-functional teams to develop prototypes for cross-portfolio use cases and support the deployment of your models or algorithms into the cloud-native production environment.
- Communicate and visualize the value of data by describing findings and techniques to both technical and non-technical audiences.
- Stay up-to-date with research and engineering developments, such as TensorFlow, PyTorch, Scikit, and Keras.
- Integrate relevant technologies and methodologies to keep our modern technology landscape up-to-date.
Requirements
- 8+ years of strong background in machine learning, data science, and software engineering.
- Proficient in Python language and experience with various ML toolkits, such as TensorFlow, PyTorch, Keras, and Scikit Learn.
- Theoretical understanding of statistical models, such as regression, clustering, and ML algorithms, such as decision trees, random forests, neural networks, etc.
- 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, and ensemble methods, performance metrics, and visualization.
- Experience working with large datasets and distributed computing systems.
- Experience in fine-tuning DL models, including LLMs, SLMs.
- Knowledge of large language models from OpenAI, such as GPT 3.5, GPT 4, Codex, etc.
- Experience with Vector Stores and RAG pipelines.
- Proficient in Data-Modelling Tools.
- Proficient in 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 to business-digestible insights.
- Excellent communication skills and experience in managing stakeholders at various levels.
- Fluent English skill is a must, German language skill is a significant advantage.
Nice to Have
- Knowledge of ML Ops, such as continuous integration, continuous deployment.
- Knowledge of full-stack development.
- Knowledge of Databricks, Data Mesh.
- Knowledge of ETL (Extract, Transform, Load) pipeline.
- Familiarity with agile methodologies, such as Scrum or Kanban, and project management tools, such as JIRA/GITLAB.
- Experience with frameworks, such as Flask/Django.
- Knowledge of Docker containers.
About EPAM
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow.
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