Azure Certified AI Practicioner with Python

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

NY

100000

120000 USD Gross Per Year

Skills

Must have

Certified Azure AI Fundamentals or Azure AI Engineer Associate (or equivalent hands-on experience)

Strong Python programming skills with experience in AI/ML libraries (e.g. scikit-learn, pandas, numpy, TensorFlow or PyTorch)

Experience using Azure AI and Machine Learning services (e.g. Azure ML Studio, Azure Cognitive Services, Azure OpenAI)

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

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)

Other

Languages

English: C1 Advanced

Seniority

Senior