Jr. Machine Learning Engineer

Job Summary

The largest health insurer in Philadelphia is seeking a machine learning (ML) operations Engineer to collaborate with our Data Scientists to refine and optimize our ML production pipelines to deliver high-quality, high-value solutions to business stakeholders. The ML Operations Engineer will evaluate and enhance our existing development and deployment processes with near real-time data and automate model performance tracking.

Responsibilities

· Work with Data Scientists to seamlessly connect the gap from development to production for our ML and NLP models under the constraints of scalability, correctness, maintainability, and efficiency

· Develop scripts and processes to optimize and automate ML and NLP models in production within Google Cloud and bring subject matter expertise about data storage and object-oriented programing

· Ensure appropriate hardware resources are selected to run models with the required latencies relative to computational cost constraints

· Develop strategies to track model performance and drift, identifying models that need to be retrained

· Document and work to standardize repeatable machine learning processes for operationalizing and automating models quickly, reliably, and reproducibly

· Collaborate with Data Scientists to extend existing ML and NLP libraries and frameworks based on team needs

· Contribute to overall development of data and CI/CD pipelines in collaboration with Data Science, Data Engineering, and DevOps teams

· Write unit tests and maintain high code quality, per both static code analysis & team standards

Technical skills

· Solid understanding of practical and theoretical aspects of standard ML and NLP concepts to enable participation in the full end-to-end pipelines for developing and deploying models effectively into production

· Experience with cloud computing environments including GCP or AWS and cloud services

· Proficiency in Python, Java, and R

· Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.

· Proficiency with ML framework such as TensorFlow, Keras, and PyTorch

· Experience in DevOps using test automation and CI/CD tools, Docker, cloud infrastructure, and other modern technologies, CI/CD pipeline set up from scratch as DevOps

· Experience with IaaS (Terraform) implementing scalable cloud / On-prem based environments and systems; service-oriented architectures and microservices; deploying resilient, scalable, high-throughput systems.

· Experience in developing and maintaining CI/CD processes for enterprise SaaS and on-prem applications using tools like GitHub, Jenkins, Maven, Gradle, GitLabs etc.

Qualifications

· 1 year experience building ML pipelines in a cloud framework, GCP preferred

· BSc in Computer Science, Software engineering, Data Science, Mathematics, or related field; Master’s degree is a plus

· Experience working with tools for collaboration, code standardization, and repeatability, and versioning (Git/Git Hub)

· Appreciation for data quality, complexity, and understanding when and how data can be used to understand business problems and questions

· Software engineer experience a plus

· Experience with health care data a plus

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Jr. Machine Learning Engineer