{"id":3157719,"url":"https://alion.io/job/trainline-senior-mlops-engineer","title":"Senior MLOps Engineer","company":{"id":4051,"name":"Trainline","domain":"thetrainline.com","url":"https://alion.io/company/trainline","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":80000,"max":107500,"currency":"GBP","period":"year","gross":null,"usd_annual":143816},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Bedrock AgentCore","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Comet ML","optional":false},{"name":"Docker","optional":false},{"name":"Evidently AI","optional":false},{"name":"Feast","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"Machine Learning","optional":false},{"name":"Metaflow","optional":false},{"name":"MLFlow","optional":false},{"name":"New Relic","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Braintrust","optional":true},{"name":"ElevenLabs","optional":true},{"name":"IAM","optional":true}],"status":"live","first_seen_at":"2026-10-23T13:52:19Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-27T08:57:10Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About us\nAt Trainline, our purpose is to empower greener travel choices, connecting people and places. Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.\nGreat journeys start with Trainline\nWe’re Europe’s leading independent rail platform, helping millions of travellers find and book the best-value rail and coach journeys across our app, website and partner channels.\nOur job is to make the green travel choice the best choice. By building a better train travel experience, we help more people choose rail - creating a positive impact for customers, our business and the planet.\nWe’re a team of more than 1,000 Trainliners from over 50 nationalities, working across London, Paris, Barcelona, Milan, Edinburgh and Madrid. Now is a brilliant time to join us and help shape the future of travel.\nIntroducing the Trainline MLOps Team\nOur MLOps team helps machine learning (ML) and AI teams across Trainline build, launch and run their products reliably. As a Senior MLOps Engineer, you will help shape how we operate AI and ML systems, including the infrastructure and tooling behind our internal ML/AI platforms and our customer-facing products. You will work on systems that are already being built and used across Trainline, so your impact will be real and visible. No two weeks look the same: one day you might be building out our ML platform, the next helping shape the architecture of our multi-agent AI products, and the next improving the developer experience with new tooling and standards. This is a hands-on role with technical leadership at its core. You will join an established team, working alongside our MLOps Engineering Manager and a small group of engineers, as we support a growing number of ML and AI teams. There is genuine scope to influence our technical direction, develop our engineering practices and mentor junior colleagues.\nIn this role as the Senior MLOps Engineer, you will...\nTake a leading technical role in helping teams across Trainline adopt and operate ML and AI tooling as the technology evolves\n\nSupport AI infrastructure, working with the teams building our internal platform and customer-facing products, making sure products are well governed, monitored and deployed through automation\n\nBuild and drive adoption of one standard way to deploy ML and AI products, so that new products onboard quickly and reach production faster\n\nAutomate the modernisation of our services across products, including fixing and preventing security vulnerabilities in libraries and dependencies\n\nStrengthen our MLOps foundations by improving cost tracking, finding ways to reduce costs, addressing security vulnerabilities and standardising engineering practices\n\nContribute to technical strategy, evaluating options and making well-reasoned decisions where there is no established approach\n\nCommunicate technical decisions clearly and help prioritise requests from the ML teams we support\n\nMentor fellow engineers and share knowledge through documentation and enablement across the organisation\n\nWe’d love to hear from you if you have...\nHands-on experience with IaC and CI/CD tooling, ideally Terraform and GitHub Actions, though alternatives such as AWS CloudFormation and Jenkins are also relevant\n\nExperience with containerised workloads using Docker and cloud platforms, ideally AWS, though GCP and Azure will be considered\n\nExperience productionising AI products, including agentic systems and the AIOps tooling behind them, ideally using AWS Bedrock AgentCore or similar\n\nExperience with managed or self-hosted ML infrastructure, such as Amazon SageMaker, feature stores (e.g. Feast) and DAG tooling (e.g. Airflow, Metaflow, or similar)\n\nExperience with model experiment tracking, ideally MLflow or Weights & Biases, and with monitoring tools such as EvidentlyAI, CometML, Grafana or New Relic\n\nExperience writing production-quality, tested Python code\n\nExperience leading or contributing significantly to major platform changes and migrations, and the ability to lead technical work through ambiguity\n\nClear communication, sound prioritisation, and a track record of getting other teams to adopt shared standards and of mentoring colleagues\n\nNice to have's...\nKnowledge of cloud topics such as networking fundamentals (VPC, security groups, CDN, WAF, etc.) and identity and access management (IAM, EntraID, SSO, etc.)\n\nExperience with any of our wider tech stack and partners, including Spacelift, Braintrust and ElevenLabs.\n\nMore information:\nEnjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme to further reduce carbon emissions, extra festive time off, and excellent family-friendly benefits.\nWe prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!\nWe're operating a hybrid model and ask that Trainliners work from the office a minimum of 60% of their time over a 12-week period. We also have a 28-day Work from Abroad policy.\nOur values represent the things that matter most to us and what we live and breathe everyday, in everything we do:\nThink Big - We're building the future of rail\n\nOwn It - We focus on every customer, partner and journey\n\nTravel Together - We're one team\n\nDo Good - We make a positive impact\n\nWe know that having a diverse team makes us better and helps us succeed. And we mean all forms of diversity - gender, ethnicity, sexuality, disability, nationality and diversity of thought. That's why we're committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated.\nInterested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor!","description_format":"text","description_chars":5973,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Dental insurance"],"hiring_locations":[{"name":"United Kingdom","iso":"GB","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Ticketing","Travel Technology"],"lifecycle":[{"event":"open","at":"2026-10-23T15:03:46Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":41,"reasons":["conf:1","velocity","win:early"],"computed_at":"2026-10-27T05:46:45Z"},"pay":{"stated_usd_annual":143816,"is_top_pay":false},"html_url":"https://alion.io/job/trainline-senior-mlops-engineer","json_url":"https://alion.io/job/trainline-senior-mlops-engineer.json","meta":{"generated_at":"2026-10-27T12:13:08Z","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":42,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"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":4051},"rest":"https://alion.io/mcp/rest/get_company?id=4051"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftrainline-senior-mlops-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"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%2Ftrainline-senior-mlops-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"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%2Ftrainline-senior-mlops-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/trainline-senior-mlops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftrainline-senior-mlops-engineer"}]}