Vitol is looking to implement and support GenAI tools, including a firmwide virtual assistant, to enhance their energy and commodities trading operations. The role aims to bridge the gap between data science, machine learning, and commercial teams, ensuring effective adoption and integration of AI tools to drive business value and facilitate the energy transition.
Requirements
- fluency in Python with ability to design and write clean, modular, well-documented code and a solid understanding of coding best practices
- Ability to logically evolve an architecture from prototype to product, considering technical debt and delivery risk
- Experience with data engineering, APIs, and cloud platforms (ideally AWS) and containerization technologies (Docker)
- Experience with enterprise software development lifecycle and tooling including continuous integration and delivery concepts/technologies
- Experience with machine learning workflows, cloud scale machine learning infrastructure (including LLMs)
- Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines
Responsibilities
- Act as the primary point of contact in Houston for our GenAI toolset
- In conjunction with the global Data Scientists deliver models and solutions to business users, and other technology teams across a wide range of projects and technologies
- Develop, test, maintain software tools and data pipelines for machine learning
- Provide software engineering and design expertise and best practices (Python) with a focus on maintainability, performance, and reliability
- As needed, take ownership of key technical infrastructure
- Engage with projects at any point in their lifecycle, understand and debug bespoke applications; driving performance and reliability
- Actively participating in and leading code reviews, experiment design and tooling decisions to help drive the team’s velocity and quality
Other
- Implement: take the requirements from our broad range of commercial stakeholders and translate these into application features.
- Design: Ensure we design and build the models and tools to meet the functional/non-functional requirements, as well as being supportable. The role will also help partner teams understand how they can support and integrate to the AI tools.
- Translate: Act as a local champion for data science and AI, helping users adopt tools and articulate their changes and requirements to the wider team.
- The individual will work both with our data scientists and machine learning engineers but will also need to directly engage with the commercial teams (across trading, operations, support functions, etc.).
- As a small team, everyone is expected to organize, prioritize and execute their own tasks; with a strong focus on maximizing the business value from their actions. This means the individual will need to be comfortable working on multiple projects simultaneously, managing competing priorities and stakeholder requirements.
