Athenahealth - Boston, MA

posted 5 months ago

Full-time - Mid Level
Remote - Boston, MA
Professional, Scientific, and Technical Services

About the position

The Senior MLOps Engineer will play a crucial role in the Machine Learning Operations (MLOps) team at athenahealth, which is dedicated to designing, developing, deploying, monitoring, and ensuring the continuous operation of the cloud-based platform that supports Machine Learning algorithms. This position is integral to the team, which focuses on operational excellence, creative problem-solving, and a commitment to helping team members succeed. The MLOps team is tasked with improving the state of healthcare by tackling complex data science and machine learning challenges, leveraging athenahealth's expansive healthcare information through advanced analytics and data science. In this role, you will be responsible for a blend of developing and deploying Machine Learning algorithms in the cloud. You will ensure that our cloud-based ML training and serving platforms are not only available and performant but also that we can proactively identify and resolve any issues that arise. Your responsibilities will include building tools that enhance the speed, confidence, and availability of our platform, as well as integrating security measures into every step of the software and infrastructure development life cycle. Collaboration across multiple technical functions will be essential to ensure high availability, disaster recovery, and customer satisfaction. The ideal candidate will be someone who strives to automate manual and repetitive operations, enjoys learning new tools and frameworks, and thrives in a highly collaborative environment. You should be organized, detail-oriented, and possess a strong customer focus, along with good communication skills and the ability to remain calm under pressure. A high sense of ownership and a proactive attitude are essential, as is a willingness to delve deep into infrastructure and code to solve problems. Enthusiasm for learning and self-starting is also a key characteristic we are looking for in a candidate.

Responsibilities

  • Develop and deploy Machine Learning algorithms in the cloud.
  • Ensure cloud-based ML training and serving platforms are available and performant.
  • Proactively identify and resolve problems with the ML platforms.
  • Build tools to improve speed, confidence, and availability of the platform.
  • Integrate security into every step of the software and infrastructure development life cycle.
  • Collaborate across multiple technical functions to ensure high availability and disaster recovery.

Requirements

  • Bachelor's degree in Computer Science or Engineering.
  • 5+ years of experience in Software/Data Engineering, MLOps, DevOps, or SRE teams.
  • Strong hands-on experience with Kubernetes for designing, creating, deploying, and maintaining ML models and services.
  • Experience in Data Science or working with Data Scientists as stakeholders.
  • Experience with model training pipelines using Kubeflow.
  • Experience deploying and maintaining Linux-based, scalable, and fault-tolerant software platforms.
  • Demonstrated experience with object-oriented programming in Python.
  • Hands-on experience with technologies such as Spark, Istio, cloud security, Terraform, or CloudFormation.
  • Experience developing microservices in a Public Cloud environment (AWS, Azure, GCP).
  • Familiarity with monitoring, log aggregation, and metrics gathering platforms (Grafana, Prometheus, CloudWatch).
  • Engineering experience with databases like Snowflake, Postgres, MySQL, Redis, DynamoDB.

Nice-to-haves

  • Familiarity with configuration management and orchestration tools (Jenkins, Puppet, Chef).
  • Experience in a highly collaborative environment.

Benefits

  • Health and financial benefits.
  • Commuter support.
  • Employee assistance programs.
  • Tuition assistance.
  • Employee resource groups.
  • Collaborative workspaces.
  • Events such as book clubs, external speakers, and hackathons.
  • Flexible work-life balance options.
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