Role overview
We are seeking a skilled and forward-looking ML Engineer with experience in Large Language Models (LLMs), generative AI, and agentic architectures to join our growing R&D and Applied AI team. This role is critical in helping Oversight deliver the next generation of agentic AI systems for enterprise spend management and risk controls.
Required
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
• 5+ years of experience building and deploying ML systems.
• Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
• Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization).
• Demonstrated experience with at least two of the following ecosystems: o OpenAI GPT models (chat, assistants, fine-tuning). o Anthropic Claude (safety-first AI for reasoning and summarization). o Google Gemini (multimodal reasoning, enterprise-scale APIs). o Meta LLaMA (open-source, fine-tuned models).
• Familiarity with vector databases, embeddings, and RAG pipelines.
• Ability to work with structured and unstructured data at scale.
• Knowledge of SQL and distributed data frameworks (Spark, Ray).
• Strong understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring.
What we're looking for
• Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
• Knowledge of AI safety, guardrails, and explainability techniques.
• Hands-on experience deploying ML/LLM solutions in cloud environments (AWS, GCP, Azure).
• Experience with CI/CD for ML (MLOps), monitoring, and observability.
• Familiarity with anomaly detection, fraud/risk modeling, or behavioral analytics.
• Contributions to open-source AI/ML projects or publications in applied ML research
If you are interested, please send your resume in English to: marlen.osorio@ust.com, including your salary expectation.