AI Engineer with Python

Direct message the job poster from Luxoft You will join the team behind an internal AI platform for processing and interacting with unstructured data. The team is currently over 30 people strong and is organized into agile teams, each of which is self-sufficient and handles the creation of features from the idea stage, through analysis, implementation, testing, production deployment, and maintenance. The team is international, and it's located in Krakow, Wroclaw, London and New York. Responsibilities: - Design, build, and optimize AI/ML solutions to process and analyze unstructured data - Collaborate with data scientists, engineers, and product teams to translate business requirements into AI features - Develop, test, and deploy machine learning models using Python and Azure Machine Learning services - Integrate models into production pipelines and monitor their performance over time - Work with large datasets and use natural language processing (NLP) techniques where needed - Ensure scalability, reliability, and performance of AI components in a cloud-native environment - Participate in code reviews, model validation, and documentation of AI solutions - Contribute to agile ceremonies and end-to-end delivery of AI features - Stay up to date with the latest Azure AI tools, frameworks, and best practices Mandatory Skills Description: - Strong Python programming skills with experience in AI/ML libraries (e.g. scikit-learn, pandas, numpy, TensorFlow or PyTorch) - Understanding of machine learning model lifecycle and deployment in cloud environments - Experience working with unstructured data (text, images, documents, etc.) - Familiarity with version control tools (e.g. Git) and CI/CD workflows - Ability to work in agile, cross-functional teams - Strong communication skills and ability to work with both technical and non-technical stakeholders Nice-to-Have Skills Description: - Experience with NLP techniques and libraries (e.g. spaCy, NLTK, Hugging Face Transformers) - Familiarity with vector databases or embedding models (e.g. FAISS, Pinecone, Azure Cognitive Search) - Knowledge of data labeling, annotation tools, or model evaluation methods - Experience with containerization (Docker, Azure Container Instances) - Understanding of MLOps practices and model monitoring strategies - Familiarity with RESTful APIs and integrating AI models into applications - Experience working with Databricks or Spark for large-scale data processing - Background in data ethics, responsible AI, or model explainability (e.g. SHAP, LIME) Seniority level

Seniority level

Mid-Senior level Employment type

Employment type

Full-time Job function

Job function

Business Development Industries

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