
11 - 50 employees
đĽ Healthcare
đ¤ Artificial Intelligence
âď¸ Healthcare Insurance
đ° $21M Series A on 2021-12
Healthcare ⢠Artificial Intelligence ⢠Healthcare Insurance
Apella is a company that offers an AI-powered surgical operations platform aimed at transforming operating rooms (ORs). Their platform helps perioperative teams make better real-time decisions, improve safety and quality processes, and optimize scheduling and staffing. By providing predictive insights and auditing key safety processes, Apella enables hospitals to enhance operating efficiency, reduce staff burnout, and improve the overall patient experience. Their solutions offer valuable analytics to address complex scheduling and utilization questions, ultimately increasing surgical volume and efficiency in ORs.
đĽ 12 hours ago
đşđ¸ United States â Remote
đľ $175k - $225k / year
â° Full Time
đ Senior
đ¤ Machine Learning Engineer
đť Ghost score 2%
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11 - 50 employees
đĽ Healthcare
đ¤ Artificial Intelligence
âď¸ Healthcare Insurance
đ° $21M Series A on 2021-12
Healthcare ⢠Artificial Intelligence ⢠Healthcare Insurance
Apella is a company that offers an AI-powered surgical operations platform aimed at transforming operating rooms (ORs). Their platform helps perioperative teams make better real-time decisions, improve safety and quality processes, and optimize scheduling and staffing. By providing predictive insights and auditing key safety processes, Apella enables hospitals to enhance operating efficiency, reduce staff burnout, and improve the overall patient experience. Their solutions offer valuable analytics to address complex scheduling and utilization questions, ultimately increasing surgical volume and efficiency in ORs.
⢠Collaborate with engineering, product, and data science teams to understand business challenges and potential machine learning and AI solutions ⢠Develop tools and automate manual processes to improve operational efficiency, accelerate experimentation velocity, and minimize human error ⢠Build, integrate, and monitor end-to-end lifecycles of large-scale, distributed machine learning systems ⢠Investigate model performance and identify data quality and performance issues ⢠Enhance the ML pipeline for the forecasting platform ⢠Manage weekly automated model retraining and deployment across production models ⢠Elevate the team's technical capabilities in MLOps best practices, automation, and production ML systems ⢠Participate in recruiter, hiring manager, and virtual onsite interviews as part of the interview process
⢠5+ years of experience building and maintaining production ML systems ⢠Deep expertise in MLOps, deployment automation, and model serving infrastructure ⢠Proficiency in Python ⢠Experience with Docker and Kubernetes ⢠Experience with CI/CD systems, including GitHub Actions and ArgoCD ⢠Experience with infrastructure-as-code, including Terraform and Helm ⢠Production ML deployment experience ⢠Experience with model training orchestration such as Dagster, Airflow, or similar ⢠Experience with automated retraining pipelines ⢠Experience with A/B testing and variant management ⢠Systems design expertise ⢠Experience building scalable microservices ⢠API design experience ⢠Experience managing complex service dependencies ⢠Track record of driving projects from concept to production, maintaining them over time, and continuously improving system reliability ⢠Experience collaborating with data scientists, backend teams, and product teams ⢠Ability to write tested, maintainable, well-documented code ⢠Experience working in healthcare or other regulated industries (nice to have) ⢠Experience with Forecasting / Time Series algorithms (nice to have) ⢠Experience with Computer Vision (nice to have) ⢠Experience with DAG frameworks and Flink (nice to have)
⢠Competitive salary ⢠Stock options ⢠Flexible vacation policy ⢠Remote-first work environment ⢠Virtual and in-person events to foster team connection ⢠Comprehensive health insurance ⢠Dental insurance ⢠Vision insurance ⢠16 weeks of parental leave for all parents ⢠Benefits and growth opportunities
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