Senior Machine Learning Engineer
AI summary of the role
Senior Machine Learning Engineer to join Vitol's data science and machine learning team, working across trading, operations, and support functions.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Design, develop, and deploy end-to-end machine learning and data science solutions across trading, operations, and support functions
- Drive adoption and development of the firm's internal GenAI chat platform as a technical lead, extending capabilities through integrations and domain-specific prompt engineering
- Apply a broad range of modelling techniques including time-series forecasting, NLP, classification, and generative AI to commodity pricing, supply/demand signals, and trade flow analysis
- Own the full data science lifecycle: data sourcing, exploratory analysis, feature engineering, model selection, deployment, and monitoring
What you’ll bring
- Master’s degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field
- 5+ years of industry experience developing and deploying machine learning or statistical models in production environments
- Fluency in Python with strong software engineering best practices (version control, testing, code review)
- Strong proficiency with ML frameworks (PyTorch, scikit-learn, Transformers) and experience with LLM-based pipelines and GenAI applications
Technologies
Python · PyTorch · scikit-learn · Transformers · AWS · Docker · Kubernetes · Airflow · Dagster · GenAI · LLM · NLP
About Vitol
Employee-owned energy and commodities trader moving oil, gas, power, metals and low-carbon fuels through global trading, logistics and infrastructure networks.
Bootstrapped · 1000–2000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and technologies. The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models. The successful candidate will join a team of experienced, collaborative practitioners, who are
More from the job description
Company Description Vitol is an energy and commodities company with revenues of $400 billion in 2023; its primary business is the trading and distribution of energy products globally – it trades over seven million barrels per day of crude oil and products and, at any time, has 250 ships transporting its cargoes. Vitol’s clients include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves clients from some 40 offices worldwide and is invested in energy assets globally including 16mm3 of storage, 480kbpd of refining capacity, and 7,000 service stations. To date, we have committed over $2.5 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world. Learn more about us here. This Role is located in Houston, TX - In office 5x a week Job Description As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and tec [... source excerpt omitted ...] flow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models. The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the ‘art of the possible’. Core Responsibilities include: Design, develop, and deploy end-to-end machine learning and data science solutions across our wider business activities (including trading, operations, and support functions) - from raw d [... source excerpt omitted ...] ng and cleaning, exploratory analysis, feature engineering, model selection and validation, deployment, and ongoing performance monitoring Build and maintain robust, well-tested, production-quality code; contribute to shared infrastructure including ML pipelines, data orchestration, and model serving layers Integrate ML and GenAI outputs into existing trading systems, dashboards, and workflows; work with software engineers to ensure reliable, scalable adoption across the business Communicate analytical findings and model outputs clearly to non-technical stakeholders; present results, assumptions, and limitations in a manner that supports confident commercial decision-making Act
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