Machine Learning

As a Machine learning engineer, you will work on utilizing and/or adapting advanced ML algorithms (supervised, unsupervised, semi-supervised, RL) to solve challenging business problem in a variety of areas including entity matching, natural language understanding, knowledge graphs and information systems. Research scientists and engineers will also design novel experiments and create implementations to enable model integration into the production stack. Seniority will be commensurate with experience and accomplishments.
Principal Duties and Responsibilities:·       Implement and scale advanced ML algorithms and incorporate recent advancements in the field to address relevant ML problems·       Adapt, customize or build-upon state-of-the-art AI/machine learning solutions to support H1’s unique ML use-cases·       Build relevant data processing capabilities and optimization workflows to support large-scale learning from multi-modal data·       Build quick Proof of Concepts (POC) and take ownership around projects to demonstrate utilization and value and drive to production-ready solutions·       Collaborate with ML scientists, engineers, and other groups within H1 to build and deploy ML solutions·       Leverage experience with systems and application development to realize ML capabilities to help build scalable, robust, resilient, automated processes
Job Requirements:·       Master’s degree in computer science, Electrical Engineering, statistics, or related quantitative discipline with a focus on Machine Learning/AI/data mining or related areas with 3+ years of experience (PhD preferred)·       Strong knowledge and understanding of foundational concepts in machine learning such as bias-variance trade-off, loss functions, regularization, model and feature selection, evaluation methodologies, optimization, and statistical testing·       Ability to implement complex machine learning algorithms and grasp the underlying mathematical framework·       Applied experience in two or more of the following areas: machine learning/AI algorithms, data mining, scalable systems (e.g. Spark), large scale data analysis, optimization, functional analysis and deep learning.·       Experience in utilizing ML and deep learning frameworks (e.g., MLLib, sklearn, Tensorflow, MxNet), AutoML techniques (e.g., hyperparameter optimization) and large-scale and distributed optimization approaches·       Strong coding skills with Python, C/C++ Scala, or any proficient ML language of choice and stacks supporting large scale machine learning·       Strong computer science skills on programming and algorithmic trade-offs·       A collaborative team player with a passion to transform healthcare for better using AI and machine Learning.

• Preferred Requirements
• PhD preferred
• Experience of applying ML in one or more of the following areas: entity matching, knowledge graphs, text analytics/NLP, information architecture (taxonomies, ontologies)
• A demonstrable track record of applying ML to build sophisticated solutions and delivered/deployed projects in the area.
• Experience with AWS stack preferred