Machine Learning Engineer
Jobot - Boston, MA
100% Remote
This Jobot Job is hosted by: Brian Raffle
Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.
Salary: $120,000 - $135,000 per year
A bit about us:
Our client wants to contribute to make the global healthcare system more sustainable. It is their strong belief that digital technologies are the key to unlocking the era of Data-Driven Medicine, where secure data pooling and knowledge sharing will be extremely valuable for patients. By helping healthcare professionals leverage their expertise and work together as a community, patients all over the world can receive equal access to better diagnoses and treatments. Combining the first two pillars of Data-Driven Medicine, Genomics and Radiomics, they can ensure that the data used to help patients today will also benefit the patients of tomorrow.
Why join us?
Medical
Dental
401K
Bonus
LTD/STD
Life
Job Details
Requirements
You are an experienced ML Engineer who is at ease working in distributed organizations as part of the technology team. You have a track record of successfully developing scalable ML models and turning these into actionable product insights. You have extensive technical skills and are up to date with the latest developments in the ML field being proficient in supervised, unsupervised, and reinforcement learning methods. You have mastery of all areas of machine learning and quantitative analysis including hypothesis generation, model selection, model development, training and validation, inference, scalability and production deployment of large-scale models, exploratory analysis, and data visualization. You are quantitative and systematic in all areas of your work. You are judicious in developing and applying the simplest statistical methods that will get the job done, instead of reaching for fashionable and unnecessarily complex. You understand how to build quality and drive continuous improvement. You are able to communicate effectively using data at all levels of the organization. You are passionate about making a difference in the lives of patients.
Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a similar field, or equivalent professional experience
Extremely solid fundamentals in statistical learning methods
At least 3 years' experience in ML engineering
Deep experience with multiple ML stacks, such as Keras, Pytorch, Tensorflow, scikit-learn
Expertise in exploratory analysis and data visualization
Expertise in building and supporting large-scale production ML models through multiple iterations.
Well-rounded software engineering experience, including a variety of technology ecosystems such as Python, Java, and C++.
Experience with genomics, digital image analysis, and clinical data analysis is an asset
Excellent interpersonal and communication skills
Knowledge of software engineering best practices (Agile, Continuous Value Delivery, CI/CD, DevOps, NoOps, PaaS, IaaS, LEAN software, Service Oriented Architecture, cloud computing)
Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.
This Jobot Job is hosted by: Brian Raffle
Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.
Salary: $120,000 - $135,000 per year
A bit about us:
Our client wants to contribute to make the global healthcare system more sustainable. It is their strong belief that digital technologies are the key to unlocking the era of Data-Driven Medicine, where secure data pooling and knowledge sharing will be extremely valuable for patients. By helping healthcare professionals leverage their expertise and work together as a community, patients all over the world can receive equal access to better diagnoses and treatments. Combining the first two pillars of Data-Driven Medicine, Genomics and Radiomics, they can ensure that the data used to help patients today will also benefit the patients of tomorrow.
Why join us?
Medical
Dental
401K
Bonus
LTD/STD
Life
Job Details
Requirements
You are an experienced ML Engineer who is at ease working in distributed organizations as part of the technology team. You have a track record of successfully developing scalable ML models and turning these into actionable product insights. You have extensive technical skills and are up to date with the latest developments in the ML field being proficient in supervised, unsupervised, and reinforcement learning methods. You have mastery of all areas of machine learning and quantitative analysis including hypothesis generation, model selection, model development, training and validation, inference, scalability and production deployment of large-scale models, exploratory analysis, and data visualization. You are quantitative and systematic in all areas of your work. You are judicious in developing and applying the simplest statistical methods that will get the job done, instead of reaching for fashionable and unnecessarily complex. You understand how to build quality and drive continuous improvement. You are able to communicate effectively using data at all levels of the organization. You are passionate about making a difference in the lives of patients.
Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a similar field, or equivalent professional experience
Extremely solid fundamentals in statistical learning methods
At least 3 years' experience in ML engineering
Deep experience with multiple ML stacks, such as Keras, Pytorch, Tensorflow, scikit-learn
Expertise in exploratory analysis and data visualization
Expertise in building and supporting large-scale production ML models through multiple iterations.
Well-rounded software engineering experience, including a variety of technology ecosystems such as Python, Java, and C++.
Experience with genomics, digital image analysis, and clinical data analysis is an asset
Excellent interpersonal and communication skills
Knowledge of software engineering best practices (Agile, Continuous Value Delivery, CI/CD, DevOps, NoOps, PaaS, IaaS, LEAN software, Service Oriented Architecture, cloud computing)
Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.