{"id":1107436,"url":"https://alion.io/job/exacare-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":5515,"name":"ExaCare","domain":"exacare.com","url":"https://alion.io/company/exacare","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"C","score":65,"open_postings":22,"ghost_share":0.591,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-29T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["CA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":92000,"max_usd":179000,"period":"year","method":"role_seniority_country_cell","sample_n":26},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bitsandbytes","optional":false},{"name":"CI/CD","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Distillation","optional":false},{"name":"Optuna","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"Ray Tune","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Docker","optional":true},{"name":"Kubeflow","optional":true},{"name":"Kubernetes","optional":true},{"name":"Mixture of Experts","optional":true},{"name":"Prometheus","optional":true},{"name":"Ray","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-03-10T21:33:41Z","employer_posted_date":"2026-03-10","last_verified_at":"2026-09-29T18:05:18Z","board_verified":true,"closed_at":null,"days_open":203,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":203},"description":"About exacare ai\nexacare ai is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, exacare ai powers more than 2,000 facilities, and is growing rapidly.\nWe recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!\n About the Role\nWe are seeking a highly adaptable, creative, and well-rounded Machine Learning Engineer to join our team. You will own the end-to-end ML lifecycle, from dataset creation and foundational research to building and deploying production-grade models. If you thrive in an environment where you can quickly iterate, experiment with cutting-edge techniques, and see your work make a tangible impact, this is the role for you.\nWhat You'll Do\nNovel Solution Development: Research, design, and implement novel machine learning solutions using modern architectures to tackle complex business problems.\nRapid Prototyping & Iteration: Build and manage efficient pipelines for rapid experimentation and hypothesis testing.\nExperiment Tracking: Methodically design, execute, and track all experiments, including hyperparameter searches, architecture changes, and data variations, using tools like MLflow or Weights & Biases.\nModel Deployment: Deploy models into production environments using CI/CD practices and model serving frameworks.\nPerformance Monitoring: Implement and maintain robust monitoring systems to track model performance, detect drift, and ensure reliability and scalability.\nAdvanced Model Optimization: Apply modern techniques to optimize models for inference speed, memory footprint, and cost. This includes quantization, pruning, and knowledge distillation\nData Lifecycle Management: Lead efforts in dataset creation, augmentation, and curation to build high-quality, robust training data.\nAdvanced Architectures: Stay current with and apply state-of-the-art techniques, especially relating to Large Language Models (LLMs)\nWhat You'll Bring\nProven experience (3+ years) in building, training, and deploying machine learning models in a production environment.\nExpert-level proficiency in Python\nExperience with modern deep learning frameworks, such as PyTorch.\nDemonstrable experience with systematic hyperparameter searching and optimization frameworks (e.g., Optuna, Ray Tune).\nExceptional organizational skills, with a strong emphasis on reproducible research and methodical experiment tracking.\nDirect experience with LLMs, including fine-tuning, prompt engineering, RAG, and efficient inference.\nPractical experience implementing model optimization techniques like quantization (e.g., bitsandbytes) and pruning\nExperience in designing and curating novel datasets from scratch.\nBachelor's or Master's degree in Computer Science, AI, Data Science, or a related technical field.\nBonus Points (Preferred Qualifications):\nFamiliarity with advanced model architectures like Transformers and Mixtures of Experts (MoE).\nContributions to open-source ML projects or a portfolio of personal projects demonstrating a passion for the field.\nStrong, hands-on understanding of the MLOps lifecycle and associated tools (e.g., Docker, Kubernetes, MLflow, Kubeflow, Prometheus).\nAn insight into our Core Values\nOnly the best belong here\nWe are unapologetic about talent. This should be the best team you have ever been on. Protecting that standard is how we honor each other’s time, ambition, and craft.\nWe work even harder to keep our partners than we did to earn them initially\nThe work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.\nWe keep the patient downstream of every decision\nAt the end of the day, this is about the patient. We get there by deeply respecting and reflecting on our purpose: to develop software that aids teams in delivering better care.\nRaise the bar on ownership\nWe grow because people here go beyond the minimum. We invest extra effort, care, and ownership into what we build.\nThe world is moving fast. We move faster.\nThis is a race. We work hard, we move early, and we stay ahead of problems and competitors. If we slow down, someone else will pass us.\nRadical candor, zero politics\nWe say what’s true, early, and we keep communication direct and clean so the team can move.\nBring good vibes and win together\nWe win as a team. We bring energy, support each other, and make the workplace somewhere people are excited to show up.\nIf this sounds like you, we'd love to have a chat!","description_format":"text","description_chars":4937,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical AI","Revenue Cycle & Medical Billing","Hospital Operations Software"],"lifecycle":[{"event":"open","at":"2026-09-22T07:00:54Z"}],"liveness":{"score":1,"band":"cold","label":"Long shot","p_open":1,"p_active":0.05,"p_room":0.28,"age_days":202,"expected_fill_days":50,"reasons":["conf:5","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-09-29T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/exacare-machine-learning-engineer","json_url":"https://alion.io/job/exacare-machine-learning-engineer.json","meta":{"generated_at":"2026-09-30T05:28:18Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3832,"day_limit":5000,"remaining_today":1168,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}