{"id":3184046,"url":"https://alion.io/job/perimeter-medical-software-engineer-ai-integration","title":"Software Engineer, AI Integration","company":{"id":4421315,"name":"Perimeter Medical","domain":"perimetermed.com","url":"https://alion.io/company/perimetermed","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-27T05:46:45Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":69000,"max_usd":147000,"period":"year","method":"role_country_seniority_unknown","sample_n":716},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Design Controls","optional":false},{"name":"Docker","optional":false},{"name":"IEC 62304","optional":false},{"name":"ISO 13485","optional":false},{"name":"ISO 14971","optional":false},{"name":"Linux","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"Verification & Validation","optional":false},{"name":"AWS","optional":true},{"name":"C++","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"Qt","optional":true}],"status":"live","first_seen_at":"2026-10-23T22:41:27Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-27T04:05:43Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"Overview\nPerimeter Medical Imaging AI is a medical technology company transforming cancer surgery with ultra-high-resolution, real-time imaging and AI-enabled technologies. Our mission is to advance the standard of care, improve patient outcomes, and reduce healthcare costs by giving surgeons enhanced visualization of microscopic tissue structures in the operating room.\nThe Software Engineer, AI Integration will play a key role in moving validated AI models and workflows into Perimeter's regulated medical device software. Embedded within the Software Engineering team, this person will build, test, integrate, and maintain reliable software, working closely with the AI and Data, Systems, and Quality and Regulatory teams. This is a hands-on delivery role, not primarily a model-research position.\nThe ideal candidate has experience developing software within a medical device QMS or a comparably regulated environment. They are equally comfortable writing well-tested Python, building automation for AI training and model delivery, and producing the verification evidence and traceability that regulated releases require.\nThis person should be excited by the opportunity to work at the intersection of AI, medical imaging, and regulated product development.\nKey Responsibilities\nDesign, implement, and maintain software features, interfaces, services, and internal engineering tools.\nPackage and integrate validated AI models and data-processing components into product software and controlled engineering workflows.\nDevelop robust interfaces between AI components, imaging systems, and other product software.\nDiagnose and resolve software defects across component and system boundaries.\nParticipate in software design discussions, code reviews, technical planning, and release activities.\nTranslate product and system needs into clear, testable software requirements and acceptance criteria.\nDevelop and maintain unit, integration, regression, and system-level test automation.\nSupport software verification and validation planning, protocols, execution, results, and defect resolution.\nMaintain requirements traceability and objective evidence throughout the software lifecycle.\nWork within Perimeter's Quality Management System, including design controls, risk management, configuration management, change control, and release documentation.\nBuild and maintain reproducible pipelines for AI training, evaluation, packaging, versioning, and delivery.\nImprove traceability across source data, annotations, code, experiments, model versions, test results, and product releases.\nAutomate cumbersome or repetitive engineering workflows while maintaining appropriate controls and review.\nSupport data ingestion, OCT labelling infrastructure, clinical QA workflows, and internal developer tools.\nMaintain containerized development and deployment environments using tools such as Docker and applicable cloud services.\nPartner with AI scientists and research interns to move validated models and prototypes into tested, supportable product components.\nPartner with Systems and Quality and Regulatory teams to identify integration risks, support design reviews, and drive release readiness.\nCommunicate technical decisions, risks, and trade-offs clearly to technical and non-technical stakeholders.\nEducation and Experience\nBachelor's degree in Computer Science, Software Engineering, Biomedical Engineering, or a related technical field, or equivalent practical experience.\n3+ years of hands-on software engineering experience building, testing, and maintaining production-quality systems.\n3+ years of experience developing software within a medical device QMS or a comparably regulated environment.\nPractical experience with software requirements, traceability, risk controls, verification and validation, defect management, and release documentation.\nFamiliarity with IEC 62304, ISO 13485, ISO 14971, or related medical device software and quality standards.\nExperience with ML lifecycle practices such as reproducible training pipelines, experiment tracking, dataset and model versioning, deployment, and monitoring preferred.\nExperience with PyTorch or TensorFlow and tools such as MLflow preferred.\nExperience working in Linux-based environments is a plus.\nExposure to medical imaging, OCT, ultrasound, or histopathology, including frameworks such as MONAI or ITK, is a plus.\nExperience building internal dashboards, annotation tools, data tooling, or developer infrastructure is a plus.\nExperience with AWS, GCP, LambdaLabs or comparable cloud infrastructure is a plus.\nRequired Skills and Competencies\nStrong proficiency in Python and the ability to write clean, maintainable, well-tested code.\nProficiency and experience with C++.\nExperience with the Qt framework is a strong plus.\nExperience with unit, integration, regression, and automated testing.\nExperience with Git-based development, code review, automated build and test workflows, and containerization using Docker.\nExperience integrating software components, services, data pipelines, or machine-learning models.\nStrong debugging and problem-solving skills across complex systems.\nClear written and verbal communication, and the ability to work effectively across multiple technical disciplines.\nSound judgment in balancing delivery speed, automation, and regulatory controls.\nDesired Attributes\nHands-on, proactive, and comfortable taking ownership of software from integration through release.\nMotivated by shipping reliable, supportable product components rather than research prototypes.\nInstinct to automate repetitive work, paired with the discipline to keep it controlled and reviewable.\nComfortable working alongside AI scientists, systems engineers, and quality and regulatory specialists.\nAble to operate in a fast-paced, growing organization.\nInterested in AI, medical imaging, and 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