{"id":2632197,"url":"https://alion.io/job/proximie-senior-mlops-engineer-2","title":"Senior MLOps Engineer","company":{"id":51652,"name":"Proximie","domain":"proximie.com","url":"https://alion.io/company/proximie","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Teamtailor","truth_index":null},"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":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":103000,"max_usd":191000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NumPy","optional":false},{"name":"OpenCV","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"timm","optional":false},{"name":"Transformers","optional":false},{"name":"Amazon ECS","optional":true},{"name":"Amazon Kinesis","optional":true},{"name":"AWS Lambda","optional":true},{"name":"AWS Step Functions","optional":true},{"name":"DynamoDB","optional":true}],"status":"live","first_seen_at":"2026-09-10T15:27:29Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-10-17T18:07:02Z","board_verified":true,"closed_at":null,"days_open":37,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":37},"description":"Proximie is on a mission to improve healthcare by transforming the world’s operating rooms into connected ecosystems of people, devices, and data.\nOur Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events - improving quality of data outputs. The result: ORs are optimised like never before - with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.\nOnce practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce - improving outcomes and saving lives.\nProximie was commercialised in 2019 and is available in over 500 facilities globally.\nCheck out our Founder and CEO Nadine’s Origins Story here: https://www.proximie.com/about-us/\nPosition Overview\nAs Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decision making, you will be the engineer who makes that intelligence dependable at scale. Using your deep technical expertise and real-world production experience, you will own the platform and the infrastructure that carry our machine learning solutions out of development and into hundreds of live hospitals, and keep them performing once they are there.\nOur machine learning engineers own the models. You own everything that gets those models in front of a customer and keeps them running: the training and deployment infrastructure on AWS and SageMaker, reproducible and configuration-driven training runs, environments defined in code, release pipelines that make a deployment routine rather than an event, and the monitoring that tells us when a model's behaviour shifts in a theatre on the other side of the world. You will make the difference between a solution that works and a solution a hospital can depend on.\nThis is a commercial team, and the work is grounded in real operational problems rather than internal roadmaps. The role demands precision, judgement and a deep understanding of how machine learning behaves in production, at scale, in environments that do not forgive downtime. If you are excited by complex problems with life-changing impact and want to build the systems that get technology like this into the most critical environments in healthcare, we would love to hear from you.\nJob Responsibilities\nTake models built by the machine learning engineers / scientists and turn them into production services that meet our latency, cost and reliability targets.\n\nBuild and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them.\n\nMake training runs reproducible and configuration-driven, so any result can be rebuilt from code.\n\nBuild monitoring for model performance, data drift and system health, and make sure the right people are alerted when something moves.\n\nShip infrastructure through code review rather than the console, using Terraform and a proper pull-request workflow.\n\nDocument what you build and raise the engineering standard around you.\n\nRequirements\nEssential\nExpert Python, with deep hands-on PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, OpenCV.\n\nProduction experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints.\n\nPractical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training runs.\n\nContainerisation and infrastructure as code: Docker and CUDA-based GPU images, plus enough Terraform to ship your own model to an environment through code review rather than a console.\n\nStrong software engineering fundamentals: Git and pull-request workflow, automated testing, CI/CD.\n\nAble to explain technical trade-offs clearly to people who are not engineers.\n\nDesirable\nEvent-driven and streaming architectures on AWS: Step Functions, Lambda, Kinesis, ECS, DynamoDB.\n\nModel monitoring in production: inference logging and drift detection.\n\nExposure to healthcare, medical devices or another regulated industry.\n\nWhy Work for Proximie?\nYou will be encouraged to grow in your role, take ownership and gain responsibilities.\n\nGenerous annual leave.\n\nTwo “well-being” days per year plus the day off for your birthday.\n\nSummer Fridays” - early office closing on Fridays during summer months.\n\nAnnual bonus programme - based on individual contribution.\n\nTo support your professional growth, all permanent employees will have access to an annual stipend of £/$1,000 to assist with personal development activities.\n\nFlexible working hours - we trust our people to manage their time and to focus on wider results.\n\nA flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.\n\nProximie is a truly global company with teams across the UK, Europe, United States, and the Middle East with that you will have opportunities to see the world.\n\nProximie is an equal opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under the law.","description_format":"text","description_chars":5957,"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":["Annual leave","Continuous learning","Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical & Healthcare Robotics","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-15T16:31:13Z"}],"visa":[{"country":"GB","licensed_sponsor":true,"evidence":"Licensed UK visa sponsor (Skilled Worker)","filings_12m":null,"filings_prev_12m":null,"green_card_filings_12m":null,"median_offered_wage_usd":null,"route":"Skilled Worker","cap_exempt":false,"checked_at":"2026-10-17T06:21:15+00:00","sources":["UK Home Office: register of licensed sponsors (workers)"],"filings_for_role_12m":0}],"liveness":{"score":41,"band":"fade","label":"Fading","p_open":1,"p_active":0.747,"p_room":0.55,"age_days":36,"expected_fill_days":36,"reasons":["conf:8","velocity","win:tail"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/proximie-senior-mlops-engineer-2","json_url":"https://alion.io/job/proximie-senior-mlops-engineer-2.json","meta":{"generated_at":"2026-10-17T19:54:23Z","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":3457,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"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":51652},"rest":"https://alion.io/mcp/rest/get_company?id=51652"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fproximie-senior-mlops-engineer-2"},{"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%2Fproximie-senior-mlops-engineer-2"},{"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%2Fproximie-senior-mlops-engineer-2"},{"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/proximie-senior-mlops-engineer-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fproximie-senior-mlops-engineer-2"}]}