{"id":4088805,"url":"https://alion.io/job/vitol-com-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":691744,"name":"Vitol.com","domain":"vitol.com","url":"https://alion.io/company/vitol-2","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"A","score":95,"open_postings":5,"ghost_share":0,"stale_share":0.2,"repost_share":0,"time_to_fill_p50_days":57,"computed_at":"2026-11-11T05:49:22Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Houston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Dagster","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Time Series","optional":false},{"name":"Transformers","optional":false},{"name":"ETL/ELT","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"RAG","optional":true},{"name":"Streamlit","optional":true}],"status":"live","first_seen_at":"2026-11-11T18:31:59Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T19:37:58Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Vitol is a leader in energy and commodities. Vitol produces, manages and delivers energy and commodities to consumers and industry worldwide. In addition to its primary business of trading, Vitol is invested in infrastructure globally, with $10+billion invested in long-term assets.\nVitol’s customers include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves its customers from more than 40 offices worldwide. Revenues in 2025 were $343bn.\nOur people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65+ nationalities and we are committed to developing and sustaining a diverse work force.\nLearn more about us here. This role is located in Houston, TX onsite 5x a week\nAs our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our AI and machine learning team. The individual will work closely with AI, 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 successful candidate will bring a strong machine learning background and have extended this expertise through hands-on delivery of GenAI projects.\nThe 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.\nThe 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’.\nCore Responsibilities include:\nDesign, 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 data ingestion through to production-grade models and monitoring\nDrive adoption and development of the firm's internal GenAI platform and applications, extending capabilities through new integrations, data connectors, and domain-specific context engineering; work closely with trading desks and operational teams to identify high-value use cases, embed the tool into day-to-day workflows, and ensure outputs are robust, and trusted by end users.\nDesign, prototype, and deploy agentic LLM workflows, including tool use and function calling; develop reusable prompts and AI Skills integrated into business workflows\nEvaluate and benchmark LLM and agentic solutions, engaging regularly with stakeholders to gather feedback and refine solutions\nApply a broad range of modelling techniques - including time-series forecasting, NLP, classification, and generative AI - to commodity pricing, supply/demand signals, trade flow analysis, and operational optimisation problems\nOwn the full data science and machine learning lifecycle on assigned projects: data sourcing and cleaning, exploratory analysis, feature engineering, model selection and validation, deployment, and ongoing performance monitoring\nBuild and maintain robust, well-tested, production-quality code; contribute to shared infrastructure including ML pipelines, data orchestration, and model serving layers\nIntegrate ML and GenAI outputs into existing trading systems, dashboards, and workflows; work with software engineers to ensure reliable, scalable adoption across the business\nCommunicate analytical findings and model outputs clearly to non-technical stakeholders; present results, assumptions, and limitations in a manner that supports confident commercial decision-making\nActively participate in code reviews, experiment design, and tooling decisions; mentor colleagues and help raise the overall standard of analytical and engineering practice across the team\nMaster’s degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field\nFluency in Python for both data science and engineering purposes: clean, modular, well-documented code, with strong understanding of software engineering best practices including version control, testing, and code review\n5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production environments\nDemonstrable experience applying a broad range of ML methodologies (supervised and unsupervised learning, time-series modelling, NLP/LLMs, optimisation) to real-world business problems\nStrong proficiency with ML frameworks (e.g. PyTorch, scikit-learn, Transformers) and experience building or consuming LLM-based pipelines and GenAI applications. Hands-on delivery of GenAI projects, including prompt engineering and agentic patterns such as tool use and function calling\nExperience with cloud platforms (AWS preferred) and modern MLOps practices: containerisation (Docker/Kubernetes), CI/CD, data pipeline orchestration (e.g. Airflow, Dagster), and model serving\nStrong analytical and problem-solving ability: capable of defining and scoping open-ended problems, proposing sound methodological approaches, and defending modelling choices with rigorous reasoning\nExcellent written and verbal communication skills, with the confidence to present model outputs, caveats, and commercial implications clearly to non-technical audiences including traders and senior management\nGenuine intellectual curiosity about commodities markets, global energy flows, and the commercial dynamics of trading; willingness to develop domain knowledge as part of the role\nDesirable Experience\nExperience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts\nExperience surfacing ML outputs through interactive tools (e.g. Dash, Streamlit, or similar) and presenting use cases to non-technical audiences, including traders and senior management\nTime-series modelling in a trading or financial context, including both ML-based and econometric approaches (e.g. ARIMA, cointegration, regime-switching models)\nExperience building retrieval-augmented generation (RAG) pipelines or multi-agent systems\nExperience building Model Context Protocol (MCP) servers or clients\nData orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines\nPrior work on LLM evaluations (evals) or model benchmarking\nPersonal Characteristics\nA self-motivated individual who thrives on seeing the results of their work make an impact in the business \nCuriosity for emerging AI developments, with a proactive commitment to continuously learning, experimenting and expanding your skills\nPragmatic and delivery-focused: comfortable navigating ambiguity, balancing rigor with speed, and making sound judgements under uncertainty\nMethodical and detail-oriented: rigorous in experimental design, data validation, and code quality, with a disciplined approach to documenting assumptions and results\nResourceful, able to think creatively and adapt in a dynamic environment\nTeam player, with an open non-political style and a high level of integrity\nDesire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world’s energy flows\nWhat we offer\nLarge diversity of projects with real-world impacts on a truly global scale\nEntrepreneurial environment within a flat hierarchy, where great ideas come to life quickly \nClose collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva)\nA highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit\nBeing part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry\nStrong management commitment to incorporating machine learning into the future of Vitol’s operations\nComprehensive benefit coverage includes:\nMedical\nDental\nVision\nPaid Vacation\n401k with company contributions\nLife insurance\nShort-term & Long-term disability\nThis role is located in Houston, TX onsite 5x a week\nAll your information will be kept confidential according to EEO guidelines.","description_format":"text","description_chars":8600,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["401k plan","Life insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Fossil Fuels","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-11-11T19:37:58Z"}],"visa":[{"country":"US","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"H-1B filings in 12 months: 5 · green card filings: 1","filings_12m":5,"filings_prev_12m":10,"green_card_filings_12m":1,"median_offered_wage_usd":150000,"route":null,"cap_exempt":false,"checked_at":"2026-11-11T07:38:50+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":3}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":57,"reasons":["conf:2","win:early"],"computed_at":"2026-11-11T21:59:53Z"},"pay":null,"html_url":"https://alion.io/job/vitol-com-machine-learning-engineer","json_url":"https://alion.io/job/vitol-com-machine-learning-engineer.json","meta":{"generated_at":"2026-11-11T21:59:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":43421,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-12T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":691744},"rest":"https://alion.io/mcp/rest/get_company?id=691744"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvitol-com-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fvitol-com-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fvitol-com-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/vitol-com-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvitol-com-machine-learning-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4088805}},{"tool":"search_jobs","arguments":{"company":"vitol.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4088805},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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