Senior Python Engineer with AI Exposure
New
D
DataArtSoftware Development
Wrocław, plac Grunwaldzki 23, Warszawa, Prosta 20, Lublin, Tomasza Zana 39a, Kraków, Jana Dekerta 24, Łódź, Gdańska 130, Wrocław, Country code: PLFull-TimeSenior
Salary12,000 - 17,000 PLN per month
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Job Details
- Languages
- En B2
- Required Skills
- AWSPythonGCPAzureRESTful APIsMLOpsGenerative AI
Requirements
- Strong proficiency in Python, including NumPy, Pandas, PyTorch, TensorFlow, and Transformers.
- Hands-on experience with LLMs, including OpenAI, Azure OpenAI, Anthropic, and Llama models.
- Experience with Agentic AI platforms (AWS Bedrock/AgentCore, Google Vertex AI, Azure AI Foundry) and frameworks (LangChain, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK).
- Experience with machine learning algorithms, natural language processing (NLP), deep learning, and vector embeddings.
- Experience with cloud platforms such as Azure, AWS, and GCP, including serverless computing services.
- Familiarity with MLOps tools such as MLflow, Kubeflow, Azure Machine Learning, Amazon SageMaker, or Databricks.
- Experience working with vector databases, including Pinecone, Chroma, FAISS, and Azure AI Search.
- Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
Responsibilities
- Design, build, and deploy machine learning and generative AI models, including LLMs, embeddings, transformers, and RAG pipelines.
- Develop scalable AI services and microservices using Python, REST APIs, and cloud native technologies.
- Optimize models for performance, accuracy, and cost efficiency.
- Build and maintain data pipelines for training, validation, and inference.
- Collaborate with data engineering teams on data ingestion, storage, and governance.
- Implement CI/CD pipelines for machine learning models and MLOps workflows.
- Monitor model performance and implement retraining strategies.
- Integrate AI systems with enterprise applications and cloud platforms such as Azure, AWS, and GCP.
- Build Retrieval Augmented Generation (RAG) architectures leveraging vector databases.
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