Autonomous Healthcare Inc.
Machine Learning Engineer (Data Science)
Autonomous Healthcare Inc., Santa Clara, California, us, 95053
At Autonomous Healthcare, we are at the forefront of medical innovation, developing the next generation of devices that will revolutionize patient care. Our mission is to commercialize breakthrough medical technologies by leveraging cutting?edge AI and autonomous systems. We believe that the best solutions are built together, and we are looking for a key member to join our collaborative R&D team.
About the Role
Autonomous Healthcare is looking for a skilled Machine Learning Engineer to join our data science team. This role is focused on diving deep into complex datasets to uncover hidden patterns and build predictive models related to pharmacy data. You will be a key player in developing and deploying solutions that directly impact our business, with a special emphasis on analyzing unlabeled data to detect critical anomalies. If you love solving challenging puzzles with data and seeing your models come to life in a production environment, we want to hear from you. Key Responsibilities Design, develop, and train machine learning models to solve complex business problems. Perform in-depth data analysis and feature engineering on large, complex datasets, with a strong focus on
unlabeled data
to identify and investigate
anomalies . Utilize
Python
and key libraries (such as
Pandas , NumPy, and Scikit-learn) for data manipulation, analysis, and model building. Manage the end?to?end machine learning lifecycle, from data sourcing and model validation to deployment. Deploy
and maintain scalable machine learning models in production on
AWS
(e.g., using SageMaker, Lambda, ECS/EKS). Collaborate with data engineers, software developers, and product managers to integrate ML models into our applications and systems. Monitor model performance, identify drift, and iterate on models to improve accuracy and efficiency.
Required Qualifications
Proven professional experience as a Machine Learning Engineer or Data Scientist. Strong programming skills in
Python
and extensive experience with data science/analytics libraries, especially
Pandas . Demonstrable experience in
analyzing unlabeled data
and building models for
anomaly detection
(e.g., using clustering, isolation forests, autoencoders, or other techniques). Practical familiarity with
deploying machine learning models on AWS
cloud infrastructure (e.g., AWS SageMaker, S3, Lambda). Solid understanding of core machine learning concepts, algorithms, and best practices including unsupervised learning and reinforcement learning frameworks. Excellent analytical and problem?solving skills.
Preferred Qualifications (A Plus)
Familiarity with
discrete event system simulation
principles or tools. Experience with other MLOps tools and cloud services. A degree in Computer Science, Data Science, Statistics, or a related quantitative field.
Seniority Level
Mid?Senior level Employment Type
Full?time Job Function
Engineering and Information Technology Industries
Hospitals and Health Care Referrals increase your chances of interviewing at Autonomous Healthcare by 2x #J-18808-Ljbffr
Autonomous Healthcare is looking for a skilled Machine Learning Engineer to join our data science team. This role is focused on diving deep into complex datasets to uncover hidden patterns and build predictive models related to pharmacy data. You will be a key player in developing and deploying solutions that directly impact our business, with a special emphasis on analyzing unlabeled data to detect critical anomalies. If you love solving challenging puzzles with data and seeing your models come to life in a production environment, we want to hear from you. Key Responsibilities Design, develop, and train machine learning models to solve complex business problems. Perform in-depth data analysis and feature engineering on large, complex datasets, with a strong focus on
unlabeled data
to identify and investigate
anomalies . Utilize
Python
and key libraries (such as
Pandas , NumPy, and Scikit-learn) for data manipulation, analysis, and model building. Manage the end?to?end machine learning lifecycle, from data sourcing and model validation to deployment. Deploy
and maintain scalable machine learning models in production on
AWS
(e.g., using SageMaker, Lambda, ECS/EKS). Collaborate with data engineers, software developers, and product managers to integrate ML models into our applications and systems. Monitor model performance, identify drift, and iterate on models to improve accuracy and efficiency.
Required Qualifications
Proven professional experience as a Machine Learning Engineer or Data Scientist. Strong programming skills in
Python
and extensive experience with data science/analytics libraries, especially
Pandas . Demonstrable experience in
analyzing unlabeled data
and building models for
anomaly detection
(e.g., using clustering, isolation forests, autoencoders, or other techniques). Practical familiarity with
deploying machine learning models on AWS
cloud infrastructure (e.g., AWS SageMaker, S3, Lambda). Solid understanding of core machine learning concepts, algorithms, and best practices including unsupervised learning and reinforcement learning frameworks. Excellent analytical and problem?solving skills.
Preferred Qualifications (A Plus)
Familiarity with
discrete event system simulation
principles or tools. Experience with other MLOps tools and cloud services. A degree in Computer Science, Data Science, Statistics, or a related quantitative field.
Seniority Level
Mid?Senior level Employment Type
Full?time Job Function
Engineering and Information Technology Industries
Hospitals and Health Care Referrals increase your chances of interviewing at Autonomous Healthcare by 2x #J-18808-Ljbffr