{"id":37382,"url":"https://alion.io/job/circadia-health-ml-research-engineer","title":"ML Research Engineer","company":{"id":16491,"name":"Circadia Health","domain":"circadiahealth.com","url":"https://alion.io/company/circadiahealth","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":77,"open_postings":6,"ghost_share":0,"stale_share":0.833,"repost_share":0.167,"time_to_fill_p50_days":35,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","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":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Edge AI","optional":false},{"name":"JAX","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"GCP","optional":true}],"status":"live","first_seen_at":"2026-02-23T20:30:59Z","employer_posted_date":"2026-02-23","last_verified_at":"2026-10-24T21:29:46Z","board_verified":true,"closed_at":null,"days_open":243,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":242},"description":"Position Overview\nAs an ML Research Engineer at Circadia Health, you will research, design, and build the next generation of models and algorithms that power our clinical monitoring platform. Circadia's devices use radar to continuously and contactlessly capture respiratory rate, heart rate, and movement data from thousands of patients - alongside audio and other physiological signals. This continuous sensing data is paired with deep clinical context from EHR integrations including conditions, medications, clinical notes, and care events, resulting in a dataset of extraordinary scale and depth that we've only begun to tap. Your work will push into novel problem domains: physiological foundation models, patient activity monitoring, radar-based bed-exit detection, and voice-based phenotyping - turning research ideas into production-grade systems that run on Circadia's devices and cloud infrastructure.\nReporting to the Principal ML Engineer, you will work at the intersection of research and engineering: formulating hypotheses, designing experiments, implementing models, and deploying them into real clinical environments. You will collaborate closely with clinical research, signal processing, and data teams to validate algorithms, define data collection requirements, and support regulatory approval.\nThis role requires a strong scientific mindset paired with a deployment-first mentality. We're looking for someone who can rapidly translate research papers into working code, iterate through experiments with rigor, and ship models that perform reliably on real patient data.\nKey Responsibilities\nResearch and develop novel models and algorithms that will form the foundation of Circadia's next-generation AI capabilities, including patient activity monitoring, physiological foundation models, radar-based bed-exit detection, and voice-based phenotyping.\nStay current with relevant ML research and rapidly prototype ideas from the literature, adapting them to Circadia's problem domains and data modalities.\nFormulate, design, run, and learn from experiments with scientific rigor, maintaining clear hypotheses, controlled comparisons, and reproducible results.\nImplement and adapt models to function effectively and efficiently in deployment environments, including both cloud infrastructure and on-device inference on Circadia's clinical monitoring hardware.\nWork with ML Ops and backend engineering teams to ensure models meet production requirements for latency, memory, reliability, and maintainability.\nOptimise models for constrained compute environments where needed (e.g. quantisation, distillation, efficient architectures).\nWork closely with clinical research teams to design validation studies, define performance benchmarks, and generate evidence to support regulatory approval.\nHelp define future-proof technical and data collection requirements in conjunction with clinical and signal processing teams, ensuring research efforts are grounded in clinical utility.\nDocument technical methods, experimental results, and architectural decisions for internal and external consumption.\nPresent research findings to technical and non-technical stakeholders, including clinical partners and leadership.\nContribute to publications, white papers, or regulatory submissions as needed.\nRequired Qualifications\nMaster's degree in Computer Science, Machine Learning, Data Science, Mathematics, or another highly quantitative field.\nAbility to write production-grade, maintainable code in Python.\nSolid understanding of classical machine learning techniques with experience applying them to real-world problems.\nStrong knowledge of deep learning methods and frameworks (e.g. PyTorch, TensorFlow, JAX) with an ability to quickly implement research papers into production-grade code.\nStrong scientific mindset: ability to rapidly iterate by formulating, running, and learning from experiments.\nStrong written and oral communication skills, both technical and non-technical.\nPreferred Qualifications\n3+ years of experience in an ML role with both research and engineering components.\nPhD in Computer Science, Machine Learning, Data Science, Mathematics, or another highly quantitative field.\nExperience with cloud computing platforms (e.g. AWS, GCP, Azure) and deployment of models into production (e.g. Docker, Flask, FastAPI).\nExperience working with data from IoT devices or sensors (e.g. radar, PPG, ECG), particularly in a medical or health context.\nExperience with (or openness to) accelerating work using AI coding tools.\nEvidence of exceptional competence through one or more of: high-quality first-author publications in AI/ML, significant open-source contributions, strong performance in ML competitions, or standout hackathon results.\nWhat You Bring\nYou combine research creativity with engineering discipline - you're as comfortable reading papers as you are shipping code.\nYou think in experiments: you form hypotheses, test them rigorously, and iterate quickly.\nYou care about clinical impact and are motivated by building technology that directly improves patient care.\nYou're comfortable working in a startup environment where you'll move fast and operate with high autonomy.\nYou communicate complex technical ideas clearly to both engineers and clinicians.","description_format":"text","description_chars":5288,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical AI","Patient Monitoring"],"lifecycle":[{"event":"open","at":"2026-02-23T20:30:59Z"}],"visa":[],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.244,"p_room":0.28,"age_days":242,"expected_fill_days":35,"reasons":["conf:0","win:tail","crowd:"],"computed_at":"2026-10-24T06:02:35Z"},"pay":null,"html_url":"https://alion.io/job/circadia-health-ml-research-engineer","json_url":"https://alion.io/job/circadia-health-ml-research-engineer.json","meta":{"generated_at":"2026-10-25T00:01:49Z","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":58,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"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":16491},"rest":"https://alion.io/mcp/rest/get_company?id=16491"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fcircadia-health-ml-research-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%2Fcircadia-health-ml-research-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%2Fcircadia-health-ml-research-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/circadia-health-ml-research-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fcircadia-health-ml-research-engineer"}]}