WSI - Machine Learning & Generative AI Engineer
WSI - Machine Learning & Generative AI Engineer
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1 Vacancy
Job Description
What youll do
- We are seeking a Machine Learning & Generative AI Engineer with strong expertise in the Azure ecosystem and Databricks combined with experience in Generative AI (GenAI) Retrieval-Augmented Generation (RAG) and agentic systems with tool use.
- The ideal candidate will be comfortable designing and deploying ML and GenAI systems end-to-end including classical ML models deep learning solutions and modern agent frameworks.
- Design implement and optimize ML and GenAI pipelines on Azure Databricks.
- Build and deploy RAG systems and agentic AI systems with tool use for enterprise applications.
- Work with Model Context Protocol (MCP) and AI Development Kit (ADK) to build scalable agentic solutions.
- Leverage frameworks such as LangChain LangGraph LangSmith and other popular GenAI EDA feature engineering and NAS experiments to improve model performance.
- Build and optimize regression classification and forecasting models using Scikit-learn XGBoost PyTorch and TensorFlow.
- Utilize GPUs for large-scale model training and inference.
- Develop deploy and monitor models and agents in production environments with proper serving and observability.
- Collaborate with data engineers product managers and stakeholders to integrate GenAI and ML solutions into business workflows.
What you know
- Strong experience with Azure Databricks and broader Azure cloud ecosystem (Data Lake Data Factory Synapse etc.).
- Hands-on expertise in Generative AI (LLMs RAG agentic frameworks tool use).
- Experience with MCP and ADK for building GenAI and agent workflows.
- Proficiency with LangChain LangGraph LangSmith and other modern frameworks for orchestration and observability.
- Solid background in Python NumPy Pandas and ML libraries.
- Experience in EDA feature engineering time-series forecasting and NAS.
- Strong knowledge of ML model development (regression classification forecasting) and deep learning frameworks (PyTorch TensorFlow).
- Familiarity with model serving MLOps practices and CI/CD for AI systems.
- Experience with GPU-enabled ML/GenAI workflows.
- Prior industry experiences deploying RAG systems and agentic AI workflows in production.
- Exposure to vector databases embeddings and semantic search.
- Familiarity with observability tools for GenAI problem-solving and communication skills with the ability to thrive in cross-functional teams.
- 5 years in ML/AI roles is preferred.
- Junior candidates with strong GenAI/agentic experience and the right mindset are also welcome.
Education
- Bachelors degree required
$30 - $40 per hour
Employment Type
Full-time
