Software Engineer (MLOps)

What you will do:

1. Help design, build and maintain ML inference infrastructure on cloud platforms like AWS and GCP.
2. Optimize ML pipelines for scalability, reliability, and fault tolerance.
3. Help maintain, expand internal Infrastructure-as-code (IaC) repositories.
4. Leverage your experience to further cultivate a strong DevOps/MLOps culture.
5. Collaborate with machine learning engineers to rapidly train and deploy ML models at scale.

Required skills:

1. Strong communication skills, with the ability to communicate complex technical concepts to both technical and non-technical stakeholders.
2. Experience working in a collaborative software development environment that includes design and code reviews.
3. Proficient in Python, scripting, infrastructure-as-code (CDK/Terraform).
4. Demonstrable knowledge of common software design patterns and principles.
5. 3-5 years of experience in data engineering, software engineering, machine learning, and/or cloud computing.
6. Hands-on experience deploying scaled ML solutions on cloud platforms like AWS/GCP and related services.
7. Knowledge of machine learning pipelines/training processes, and frameworks like MLFlow.
8. Experience in a DevOps/MLOps role, configuring and launching docker containers, CI/CD, scheduling and orchestration frameworks (argo workflows/airflow/luigi/dagster/etc.).
9. Demonstrated ability to learn and adapt to new technologies, tools, and best practices.

Other Requirements:

1. Bachelor's degree in computer science, engineering, or related field.
2. Willingness to work full time in-person at our Somerville, MA Office.