AI Engineer with Python
- Belgrade
- Cluj-Napoca
- Krakow
- Larnaca
- Lodz
- Lublin
- Remote.Bulgaria
- Remote.Georgia
- Remote.Poland
- Riga
- Sofia
- Tbilisi
- Varna
- Warsaw
- Wroclaw
- Yerevan
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Position overview
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.
- Work with structured and unstructured datasets for feature engineering, vectorization, and model training.
- Build 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 drift, and implement retraining strategies.
- Manage model lifecycle processes, logging, and observability.
- Integrate AI systems with enterprise applications, APIs, and cloud platforms such as Azure, AWS, and GCP.
- Build Retrieval Augmented Generation (RAG) architectures leveraging vector databases such as Pinecone, FAISS, Weaviate, or Azure AI Search.
- Ensure solutions align with enterprise security, compliance, and responsible AI standards.
- Work with product, engineering, domain experts, and business teams to translate requirements into technical solutions.
- Communicate AI capabilities and limitations to non technical stakeholders.
- Conduct proofs of concept (POCs), demonstrations, and conceptual solution design activities.
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 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.
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Vacation
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Health insurance
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Sick pay
10 days without a doctor's note, afterwards - as per the laws of your country
Time off for state holidays
According to the official calendar, regardless of the client’s schedule
Pleasant environment
Two large corporate parties and many small get-togethers for colleagues
Comfort service
Solving technical and everyday problems at work
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