Senior Python Engineer with AI Exposure
DataArt
Position overview
We are seeking a skilled Senior Python Engineer to design, develop, and deploy AI and ML driven solutions that enhance business capabilities, automate processes, and improve customer and employee experiences. The ideal candidate has a strong foundation in machine learning, large language models (LLMs), data engineering, and cloud platforms, with the ability to productionize models at scale.
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.
What We Offer:
Vacation days: Up to 26 business days per year.
10 illness/special days
off per year (fully paid, no medical papers needed) for all contract types
Health and life insurance (Luxmed)
MyBenefit platform with Multisport option
Internal psychological support service
English language classes from the first working day
Access to external learning platforms: O'Reilly, LinkedIn Learning, Udemy, and a wide catalog of diverse internal training
Flexible workplace: work from the office, from home, or choose a hybrid option
Tech Skills Mentoring Program
Opportunities to develop as a public speaker, mentor, or technical interviewer
Fully paid idle (bench) when not involved in a project
Certification reimbursement (AWS, GCP, Microsoft, etc.)