About the role

Role Overview

Machine Learning Engineer responsible for turning analytical models into scalable, production-ready solutions. You will collaborate with Data Science and IT teams to build data pipelines and deploy ML models that drive measurable business impact.

Responsibilities

Transform analytical models into production-ready ML solutions
Build and maintain robust data pipelines
Support model migration and model productionization
Deploy models using modern tooling and automation (CI/CD and infrastructure)
Collaborate cross-functionally with data science and IT stakeholders

Required Skills

5–6 years of experience in machine learning and data engineering
Strong proficiency in Python and SQL
Understanding of CI/CD automation, pipelines, and deployment
Hands-on experience with:
- Airflow
- Vertex AI
- Dataform
- GitHub Actions
- Terraform
- Kubernetes
Knowledge of model migration, productionization, and data pipeline implementation

Nice to Have

Experience with GCP (Google Cloud Platform)
Familiarity with MLflow, Kubeflow, or SageMaker

Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
Proven track record supporting model deployment and migration
Experience working in a collaborative, cross-functional team environment

Other Requirements

Ability to work remotely with a standard EST 9am–5pm schedule
Strong communication skills and a proactive, hands-on approach
Willingness to complete technical assessments and live coding interviews

About Optomi

Optomi is a staffing and recruiting firm that supports companies in building teams across technology and data. This role is positioned within an AI and machine learning innovation environment, working closely with data science and IT teams to productionize analytics and models.

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