Remote ML/Data Pipeline Tech Leader — Scale & Impact

BairesDev; United States; Remote; MXN 2,793,000 - 4,283,000; Full time

Benefits offered by this job

Remote work

Competitive USD-based compensation

Home-office setup provided

Flexible hours

Paid holidays

Mentorship and growth opportunities

Job summary

BairesDev is hiring a Machine Learning + Data Pipeline Technical Leader to own and redesign scalable data pipelines for foundation-model training data. You will diagnose and re-architect pipelines end-to-end, guiding a team of engineers with a focus on scalable, efficient, multimodal data.

Lead design decisions, establish observability practices, and drive reliability across the data platform. 100% remote, competitive USD-based compensation, and global collaboration with top talent.

Qualifications

• 8+ years in ML engineering or data pipeline engineering.
• Strong Python for ML/AI, with deep Ray experience.
• Ability to diagnose and re-architect pipelines end-to-end.
• Design for scale and efficiency on large heterogeneous multimodal data.
• Background in data observability, traceability, and reliability.
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Responsibilities

• Own and redesign scalable data pipeline architecture for foundation-model training data.
• Diagnose and re-architect failing or inefficient pipelines end-to-end.
• Design for scale and efficiency across large multimodal data.
• Anchor technical design decisions and guide implementers.
• Establish data observability, traceability, and reliability practices as a discipline.

Skills

Python for ML/AI

Ray

Data pipeline design

Technical leadership

Kubernetes

Distributed compute

English proficiency

Tools

Spark

Job description

BairesDev is hiring a Machine Learning + Data Pipeline Technical Leader to own and redesign scalable data pipelines for foundation-model training data. You will diagnose and re-architect pipelines end-to-end, guiding a team of engineers with a focus on scalable, efficient, multimodal data.

Lead design decisions, establish observability practices, and drive reliability across the data platform. 100% remote, competitive USD-based compensation, and global collaboration with top talent.