Senior Data Engineer — AI/ML Pipelines, Remote

Remote DXB; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical, dental & vision insurance

401(k) with matching

Paid time off & holidays

Parental bonding leave

Professional development reimbursement

Remote work equipment reimbursement

Monthly internet/phone reimbursement

Job summary

Octave is seeking a data/ML engineer to design, build, and maintain scalable data pipelines and ML workflows within a behavioral health context. You will implement automation and tooling to accelerate development while ensuring observability and production readiness.

Join a team that mentors peers and applies AI tooling to improve decision-making, with a focus on healthcare data pipelines and compliant data handling.

Qualifications

• 5+ years of experience in data engineering, platform engineering, or ML engineering.
• Proficiency in SQL and Python.
• Experience with data ops best practices, monitoring, and CI/CD.
• Experience with GCP or AWS data engineering tools and big data frameworks.
• Experience with data modeling and medallion architecture.
• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering or a related field.

Responsibilities

• Design, build, and maintain scalable systems for data ingestion, transformation, and storage.
• Implement frameworks, tooling, and automation to increase development velocity.
• Develop end-to-end AI/ML workflows from source ingestion to downstream systems integration.
• Support iterative model development, production operations, and observability.
• Mentor peer engineers and contribute to a culture of continuous improvement.
• Leverage AI tools to improve efficiency and decision-making.

Skills

SQL

Python

DataOps

CI/CD

Education

Bachelor's degree

Tools

GCP

AWS

Job description

Octave is seeking a data/ML engineer to design, build, and maintain scalable data pipelines and ML workflows within a behavioral health context. You will implement automation and tooling to accelerate development while ensuring observability and production readiness.

Join a team that mentors peers and applies AI tooling to improve decision-making, with a focus on healthcare data pipelines and compliant data handling.