Machine Learning Engineer III

ARG - Remote

Teladoc Health

The telehealth solution more people and organizations trust for a full range of healthcare needs, with over 50 million virtual visits and 20 years of experience.

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Teladoc Health is a global, whole person care company made up of a diverse community of people dedicated to transforming the healthcare experience. As an employee, you’re empowered to show up every day as your most authentic self and be a part of something bigger – thriving both personally and professionally. Together, let’s empower people everywhere to live their healthiest lives.

Machine Learning Engineer - Product Lifecycle & Intervention

The opportunity

The machine learning effort is part of the Data Science team at Teladoc Health. In your role as a Machine Learning Engineer, you will work closely with machine learning scientists, data engineers, backend/frontend engineers and different stakeholders to create, deploy and maintain scalable data processing, machine learning pipelines and services that drives Teladoc Health’s products and business forward. Your efforts and your team’s contributions will have a big impact on leading personalized whole-person virtual care by better understanding members from diverse data sources.

This is an opportunity to use technical rigor to apply scalable data processing tools and machine learning algorithms to real-world business problems; and engineer, deploy, measure and iterate AI / ML in production.


Responsibilities

· Design, develop, deploy, and maintain production-grade scalable data transformation, machine learning and deep learning code, pipelines, and operation dashboards; manage data and model versioning, training, tuning, serving, experiment, and evaluation tracking dashboards.

· Design and implement appropriate data warehouses and schemas for the ETL and machine learning pipelines. Manage ETL and machine learning model lifecycle: develop, deploy, monitor, maintain/debug, and update data and models in production.

· Use Python, SQL, Spark, Tensorflow, and PyTorch to write clean, reusable, and robust code for data-engineering and machine learning pipelines. This includes data transformation, feature engineering, unsupervised learning, supervised learning, and reinforcement learning.

· Implement engineering solutions end to end including CI/CD, Scaling, Logging, Monitoring of Services, Alerting, Modeling work, Product integration, E2E testing, and defining SLAs between microservices.

· Promote and role-model best practices and framework of ML model development, testing, evaluation, operation and experimentation, etc. within the team and beyond.

Candidate Profile

· Self-driven individual with extensive experience in building and scaling maintainable software, data processing, feature extraction and construction and machine learning pipelines including model training, serialization, evaluation, interpretation and experimentation.

· 6+ years’ experience in Machine Learning Engineering roles in SaaS or consumer companies

· A Master’s degree or higher in computer science, machine learning, information systems, engineering, or a related field.

· Ability to write clean, robust and re-usable code in Python, Spark and SQL. Familiarity with big data platforms (like Spark) , machine learning frameworks (like Tensorflow, Keras or PyTorch) and libraries (like scikit-learn).

· Familiarities with the cloud platform, ETL, ML pipeline and API service tools like Azure, AWS, Jenkins, Databricks, sagemaker, MLflow, Flask, Airflow or similar.

· Deep knowledge of probability, statistics, and ML algorithms. Familiarity with deep learning, contextual bandits/reinforcement learning, and generative AI with experimentation experience in production would be a plus.

· Experience with agile sprint processes to deliver ML work.

· Willingness to learn new ML platforms and tools, as well as propose and help teams adopt new tools. Willingness to expand the scope to work with backend/frontend engineers, DevOps partners to solve the problem as needed.

· Great active listening skills to infer product needs and underlying context.

· Ability to collaborate effectively with peers, and respect for member privacy.

#LI-Remote #LI-Arg  #LI-MLD

Why Join Teladoc Health?


A New Category in Healthcare:  Teladoc Health is transforming the healthcare experience and empowering people everywhere to live healthier lives.  

Our Work Truly Matters: Recognized as the world leader in whole-person virtual care, Teladoc Health uses proprietary health signals and personalized interactions to drive better health outcomes across the full continuum of care, at every stage in a person’s health journey.  

Make an Impact: In more than 175 countries and ranked Best in KLAS for Virtual Care Platforms in 2020, Teladoc Health leverages more than a decade of expertise and data-driven insights to meet the growing virtual care needs of consumers and healthcare professionals.  

Focus on PEOPLE:  Teladoc Health has been recognized as a top employer by numerous media and professional organizations. Talented, passionate individuals make the difference, in this fast-moving, collaborative, and inspiring environment. 

Diversity and Inclusion:  At Teladoc Health we believe that personal and professional diversity is the key to innovation. We hire based solely on your strengths and qualifications, and the way in which those strengths can directly contribute to your success in your new position.  

Growth and Innovation:  We’ve already made healthcare yet remain on the threshold of very big things. Come grow with us and support our mission to make a tangible difference in the lives of our Members.  

 

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status or pregnancy.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Airflow APIs AWS Azure Big Data CI/CD Computer Science Databricks Deep Learning DevOps Engineering ETL Feature engineering Flask Generative AI Keras Machine Learning Microservices MLFlow ML models Model training Pipelines Privacy Python PyTorch Reinforcement Learning SageMaker Scikit-learn Spark SQL Statistics TensorFlow Testing Unsupervised Learning

Perks/benefits: Career development Startup environment

Region: Remote/Anywhere
Job stats:  21  3  0

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