Machine Learning Engineer III

Glidewell Laboratories is the industry leader in dental technology due to our agility, speed, and cutting edge technology.

We work in a fast-paced and highly sought-after employee-friendly work environment. Behind all of this success is an amazing group of people who are passionate about bringing innovation to the marketplace, while providing quality and affordability to better the lives of people all over the world.

If you share in our passion for teamwork and a vision for excellence, let's talk about a rewarding career at Glidewell!In addition are the following generous employee benefits : Medical, Dental, Vision, 401K with company match, company-paid life insurance, additional onsite dental services, vacation, holiday, and sick time, employee gym (with fitness classes and meditation room), employee medical / wellness center (with massage therapy and acupuncture), two company subsidized cafes, Internet cafes, employee lounges with big screen TVs, game tables, fun company sponsored events, a diverse work environment with over forty nationalities represented, and much more!Essential Functions : Builds, deploys, monitors, and continuously optimizes ML models and developing automated ML models’ training and inference pipelines.

Builds a deep understanding of the Company’s products, services, data and customers to facilitate development of personalized and fulfilling experience.

Researches, designs, and prototypes robust and scalable models based on machine learning, data mining, and statistical modeling to answers key business problems.

Build tools and support structures needed to analyze data, perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.

Dives into machine learning engineering and researching topics including ML algorithms, feature engineering, analysis, modeling, and production deployment.

Uses predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

Works with other machine engineering leads to continue to mature the use of machine learning within the organization.Develops training and cross-validation data sets for machine learning algorithms.

Translates product management, engineering and business contraints and queries into tractable data science questions.Identifies new opportunities of applying ML technology to improve the business workflows and processes.

Mentors and trains lower level engineers.Performs other related duties and projects as business needs require at direction of management.

Education and Experience : Master’s degree in Machine Learning, Deep Learning or a computer science-related field. PhD preferred.

Minimum eight (8) years of relevant work experience.Understands fundamental concepts, practices and procedures of ML field.

Data discovery, data aggregation and feature engineering with excellent SQL query writing skills.Training, evaluating, optimizing, deploying and maintaining machine learning models on production systems.

Logging, tracking, A / B testing, evaluate and analysis the performance of different ML algorithms and models on production systems.

Application developing and strong development skills in Python programming language and have experience on developing data-driven, scalable and reliable applications with AWS.

Applying machine learning algorithms to solve a wide range of optimization problems like customer sales prediction, recommendation engine, sentiment analysis, deep learning with image and natural language, customer segmentations / clustering, object detection.

Utilization of popular open source ML / Deep learning libraries like MxNet / Gluon, Tensorflow, scikit-learn, pandas, pyTorch, Keras, xgboost, LightGBM, Turi Create and Nvidia Digits.

Experience working with relational, non-relational, and high-scale data processing and storage frameworks like SQL, AWS RedShift, Aurora, S3, DynamoDB, MySQL, PostgreSQL.

Experience with AWS Serverless architecture and AWS native services like EC2, Lambda, Step Functions, SageMaker, DeepLens, Rekognition, IoT, GreenGrass, Comprehend, Lex / Polly and Transcribe.