Software Engineer (ML)

Role: Software Engineer (ML)

Location: Remote

Utilizes complex knowledge of machine learning engineering concepts and principles to apply skills in a business environment. Primarily focused on productionizing machine learning models and systems at scale. Performs work independently or with minimal guidance, depending on task complexity. May function as technical lead on assigned projects.

Essential Job Functions:

1. Delivers specific ML Ops engineering tasks such as moderate to complex level designing, developing, implementing, optimizing, and maintaining models, systems, and applications using existing and emerging technology platforms.
2. Collaborates with cross-functional architecture teams to define and integrate frameworks and roadmaps for machine learning solutions. Projects are generally of moderate complexity. Consults on the design, development, and implementation of DevOps and ML Ops pipelines. May lead portions of deployment processes under guidance from people leader. Reviews, verifies, validates, and troubleshoots code to ensure high availability and high performance of machine learning models and applications. Uses complex knowledge and understanding of code management principles and best practices to follow architectural and governance guidelines. Effectively communicates and applies machine learning engineering value, concepts, and strategies across multiple scenarios.

Additional Qualification:

1. Demonstrated analytical skills. Demonstrated problem solving skills. Possesses strong technical aptitude.
2. Experience with: building and maintaining end-to-end machine learning pipelines in production environments.
3. Experience with model and data versioning, model deployment, model serving and monitoring. Intermediate knowledge of workflow orchestration processes and technologies. Ability to simultaneously handle multiple priorities. Seeks to acquire knowledge in area of specialty.

Special Skill Requirements:

1. Strong Coding experience.
2. Python
3. Object Oriented Programing
4. AWS – SageMaker
5. Git, GitHub

Additional Qualification:

1. Demonstrated analytical skills. Demonstrated problem solving skills. Possesses strong technical aptitude.
2. Experience designing and building scalable enterprise ML Ops frameworks and pipelines including integration, testing, deployment, monitoring, infrastructure management, audit and governance.
3. Advanced understanding and practical application of workflow orchestration processes and technologies. Ability to simultaneously handle multiple priorities. Seeks to acquire knowledge in area of specialty.
4. Highly thorough and dependable.
5. Effectively coaches and delivers constructive feedback.

Education Requirements:

1. High School Diploma or equivalent required. Bachelor's degree preferred.