Company

PointclickcareSee more

addressAddressUnited States
type Form of workFull-time
salary Salary$171,000 - $193,000 a year
CategoryInformation Technology

Job description

For more than 20 years, PointClickCare has been the backbone of senior care. We’ve amassed the richest senior care dataset making our market density untouchable and our connections to the healthcare ecosystem exponentially more powerful than those of any other platform.

With Collective Medical & Audacious Inquiry, we’ve become the most expansive, full-continuum care collaboration network, offering care teams immediate, point-of-care access to deep, real-time insights at every stage of a patient’s journey.

For more information on PointClickCare, please connect with us on Glassdoor and LinkedIn.

Location: US (Remote)

As a Senior Applied Researcher – Machine Learning within the PointClickCare Advanced Technology team, you will work with customers, product leaders, subject matter experts, other highly experienced Applied Researchers, engineers, or others on cutting-edge research and development projects to address the needs of users in the acute, post-acute, long term and cross-continuum care space to truly transform healthcare.
Examples of typical project areas and responsibilities include end to end responsibilities for developing, improving, and validating new machine learning models, working with other researchers to improve and validate the performance of machine learning models, and working with engineers on infrastructure to support the automated deployment and management of models or incorporating models into large scale commercial SaaS products. This role will involve hands-on work in one or more applied machine learning technology areas such as machine learning, deep learning, Natural Language Processing including Large Language Models and other Transformer models, or other advanced technologies. Relevant industry experience and Python skills are required.
Responsibilities:
  • Perform research, experimentation, and related engineering to design, build and evaluate machine learning and NLP-based models to be deployed into production environments,
  • Tasks may include (for example) data collection, data cleaning, data analysis, model training, development, and evaluation, and scaling up the system.
Required Experience:
  • Master’s degree or equivalent experience in Computer Science, Math, Physics, Engineering or a related field and experience with advanced mathematics or statistical methods applicable to machine learning and NLP
  • Proven industry experience, through multiple major product releases
  • Proficiency in Python
  • Experience doing data engineering for ML and NLP applications, including exposure to database systems and proficiency with SQL.
  • Exposure to building models from big data using modern machine learning and NLP packages and data analysis stacks such as NumPy, SciPy, Scikit-learn, Pandas, Keras, Tensorflow, PyTorch, CNTK or NLTK, and experience such as fine tuning LLMs or other Transformer based models
  • Curious problem finder and problem solver, able to think both creatively and methodically.
  • Strong interest in applying machine learning and NLP to healthcare-related problems and data.
  • Works well with others and independently and comfortable working on a distributed team
Helpful Experience:
  • Experience working with large data sets using big data processing frameworks (e.g. Azure Data Lake, HDFS/Hadoop, Spark or other cluster computing/MapReduce frameworks) and/or public cloud infrastructure (Azure, AWS, Google Cloud) for building, evaluating, or deploying machine learning and NLP models, including experience with end to end SaaS-scale ML/NLP pipelines, is a plus.

$171,000 - $193,000 a year
At PointClickCare, base salary is one of the many components that make up our total rewards package. The USD base salary range for this position is $171,000-193,000+ bonus + equity + benefits. Our salary ranges are determined by job and level. The range displayed on each job posting reflects the target for new hire salaries for the position across all USD locations. Within the range, individual compensation is determined by job-related skills and knowledge, relevant experience including professional and lived experience, and/or work location. Your recruiter can share more information about our total rewards package during the hiring process.

It is the policy of PointClickCare to ensure equal employment opportunity without discrimination or harassment on the basis of race, religion, national origin, status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, veteran status, genetic information, or any other basis protected by law. PointClickCare welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. Please contact recruitment@pointclickcare.com should you require any accommodations.

When you apply for a position, your information is processed and stored with Lever, in accordance with Lever’s Privacy Policy. We use this information to evaluate your candidacy for the posted position. We also store this information, and may use it in relation to future positions to which you apply, or which we believe may be relevant to you given your background. When we have no ongoing legitimate business need to process your information, we will either delete or anonymize it. If you have any questions about how PointClickCare uses or processes your information, or if you would like to ask to access, correct, or delete your information, please contact PointClickCare’s human resources team: recruitment@pointclickcare.com

PointClickCare is committed to Information Security. By applying to this position, if hired, you commit to following our information security policies and procedures and making every effort to secure confidential and/or sensitive information.
Refer code: 8826699. Pointclickcare - The previous day - 2024-04-01 07:19

Pointclickcare

United States
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