Senior Remote MLOps Leader for Production ML Systems

Jaggle.AI; United States; Remote; USD 170,000 - 290,000; Full time

Benefits offered by this job

Remote work options

Health insurance

Wellness benefits

Professional development budget

Conference and publication support

Job summary

Jaggle.AI is seeking aSenior ML Engineer to lead the design, development and deployment of AI-driven project management systems. You will own ML pipelines, production models and scalable infrastructure, while mentoring engineers and data scientists and translating product needs into effective ML solutions.

The role emphasizes distributed training, model optimization and cutting-edge NLP applications, with remote-friendly setup and opportunities to speak at conferences and publish.

Qualifications

• Minimum seven years of ML engineering experience.
• Master's or doctoral degree in CS, ML or related field.
• Expert in PyTorch or TensorFlow; strong Python and software skills.
• Experience with NLP, transformers and large language models.
• Proven deployment of ML models to production at scale.
• Expertise in MLOps, model monitoring and versioning; distributed training experience.

Responsibilities

• Design and build ML systems, pipelines and scalable workflows.
• Develop, deploy and maintain production-grade models.
• Research and apply current ML methods to product needs.
• Improve model performance, latency and resource use; distributed training and optimization.
• Establish practices for model versioning, monitoring and MLOps.
• Mentor ML engineers and data scientists and collaborate with product teams.

Skills

ML engineering

Python

Software engineering

NLP

Education

Master's or PhD in CS/ML

Tools

PyTorch

TensorFlow

Distributed training

MLOps

Model monitoring

Job description

Jaggle.AI is seeking aSenior ML Engineer to lead the design, development and deployment of AI-driven project management systems. You will own ML pipelines, production models and scalable infrastructure, while mentoring engineers and data scientists and translating product needs into effective ML solutions.

The role emphasizes distributed training, model optimization and cutting-edge NLP applications, with remote-friendly setup and opportunities to speak at conferences and publish.