Machine Learning Engineer

3 weeks ago

Philadelphia, United States Brooksource Full time

Machine Learning Engineer

Philadelphia, PA

Hybrid(3 days onsite)

Contract to hire

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 programming
  • 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:

  • 2-3 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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