{"id":2676607,"url":"https://alion.io/job/xantura-senior-ml-ops-engineer","title":"Senior ML Ops Engineer","company":{"id":685225,"name":"Xantura","domain":"xantura.com","url":"https://alion.io/company/xantura","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Pinpoint","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":null,"salary_estimate":{"min_usd":106000,"max_usd":197000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":40},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"GDPR","optional":false},{"name":"Grafana","optional":false},{"name":"Kubernetes","optional":false},{"name":"NLP","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prefect","optional":false},{"name":"Prometheus","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Qdrant","optional":true}],"status":"live","first_seen_at":"2026-10-15T05:15:14Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-22T05:25:16Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"In this role you will work in the Platform team - a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.\nKey Responsibilities\n\nAs an MLOps Engineer, you'll own the infrastructure layer that all of Xantura's AI services depend on to operate and scale. You'll be responsible for how ML models and NLP systems are deployed, monitored, and maintained across a growing base of local authority clients, ensuring that what works for one client works reliably for a hundred.\n\nYou'll work across every pillar of the AI function - predictive modelling, text analytics, knowledge representation, and agentic AI - building the deployment pipelines, orchestration, and observability that enable the rest of the engineering team to ship with confidence.\n\nKey responsibilities\n\nContinuously evolve the platform infrastructure powering all AI services (predictive modelling, NLP, knowledge representation, and agentic AI), ensuring reliable, scalable operation across a growing base of local authority clients.\nDeploy and manage ML models via Azure ML endpoints, batch endpoints , and AKS, enabling resilient, secure model hosting that accelerates client onboarding and ensures models remain performant and monitorable throughout their lifecycle.\nEnsure all ML systems are transparent, explainable, and auditable, aligned with Responsible AI principles and UK GDPR; essential where AI outputs inform decisions about vulnerable people in health and social care.\nDesign, build, and maintain production-grade orchestration pipelines (Dagster) supporting model training, inference, and retraining, ensuring data from local authority systems is timely, accurate, and fit for purpose before it reaches ML services.\nContribute to organisation-wide AI capability building, sharing best practice with delivery and consulting teams, advising on technical feasibility, and shaping governance standards as the AI function scales.\n\nWhat are we looking for?\nWe’d love to hear from you if you have:\nBachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.\n4+ years of professional experience in an MLOps, Platform Engineering, or Infrastructure Engineering role supporting ML or data-intensive systems.\nStrong programming skills and production experience in Python. \nExpertise in Azure-native MLOps, including model endpoints, pipelines, registries, environments, and compute management.\nClear evidence of practical experience across the following:\nDeploying, scaling, and troubleshooting containerised workload on Kubernetes in production\nBuilding and maintaining CI/CD pipelines (Azure DevOps or equivalent) for automated testing, building, and deployment of ML services\nImplementing infrastructure-as-code (Terraform, Bicep or Pulumi)\nImplementing monitoring and observability for production systems, including metrics, altering, logging, and dashboarding (e.g. Prometheus, Grafana)\nPipeline orchestration using Dagster, Airflow, Prefect, or similar\n\nBonus points if you have:\nPractical experience with model serving infrastructure - batch and/or real-time inference at scale.\nExperience operating multi-tenant systems, particularly scaling infrastructure across multiple clients or business units.\nPractical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services. \nExperience setting up, and optimising vector databases, e.g. Qdrant, and integrating with other services\nProficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD). \nDeep familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault).\n\nLocation - This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is also required for on-site client engagements as needed.\nWhat can we offer you?\nCompetitive salary reviewed annually\nWork for a passionate, mission-driven company solving society’s big problems\nWork flexible hours around life commitments with a focus on delivering company value rather than hours worked\nAbility to work remotely (excluding face-to-face Team Meetings and client meetings)\nTraining and development opportunities\n25 days annual leave (plus bank holidays)\nCompany pension\nPrivate medical insurance\nGenerous enhanced parental leave policies\nCycle to work scheme\nFlu Vaccinations,\nEye Test and contribution towards Glasses for VDU use\nEmployee Assistance ProgrammeMental health and wellbeing support\nRemote GP access\nCounselling/therapy\nPhysiotherapy\nMedical second opinions","description_format":"text","description_chars":4828,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Annual leave","Health insurance","Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Digital Government","Data Marketplaces, Sharing & Clean Rooms"],"lifecycle":[{"event":"open","at":"2026-10-16T05:15:14Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":7,"expected_fill_days":30,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/xantura-senior-ml-ops-engineer","json_url":"https://alion.io/job/xantura-senior-ml-ops-engineer.json","meta":{"generated_at":"2026-10-22T08:09:42Z","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":4256,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"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":685225},"rest":"https://alion.io/mcp/rest/get_company?id=685225"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fxantura-senior-ml-ops-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%2Fxantura-senior-ml-ops-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%2Fxantura-senior-ml-ops-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/xantura-senior-ml-ops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fxantura-senior-ml-ops-engineer"}]}