MLOps Engineer, JAX, PyTorch, Pallas/Triton

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with research and engineering teams to enhance AI model capabilities in MLOps, ML infrastructure, and extensive training systems.

• Create challenging, real-world machine learning systems and MLOps tasks that mirror production engineering scenarios.

• Develop precise and well-documented solutions for intricate ML infrastructure and training pipeline challenges.

• Assess and review technical tasks and AI-generated solutions, offering clear and actionable written feedback.

• Establish comprehensive evaluation rubrics and scoring frameworks for areas such as:

• - Distributed training architectures

• - ML pipeline design

• - Infrastructure optimization

• - Kernel-level programming

• - Performance tuning

• Work alongside fellow subject matter experts to ensure consistency, quality, and technical accuracy within training datasets.

• Provide domain expertise to enhance the reasoning capabilities of sophisticated AI systems.

⛳️ Requirements

• At least 2 years of professional experience in MLOps, Machine Learning Infrastructure, or ML Systems Engineering within a reputable technology organization.

• Hands-on production experience with JAX and/or PyTorch in large-scale machine learning settings.

• Practical experience in developing or optimizing custom GPU kernels utilizing Pallas (JAX) or Triton.

• Strong comprehension of distributed training systems, model optimization, and scalable ML infrastructure.

• Proven career progression and increasing technical responsibility.

• Availability to work 40 hours per week during standard weekday business hours.

• Exceptional written communication skills with the ability to articulate technical concepts and architectural decisions clearly.

• Experience in designing and optimizing extensive ML training pipelines.

• Knowledge of distributed computing and GPU performance enhancement.

• Familiarity with evaluation methodologies for AI models and ML systems.

• Experience collaborating with research teams on advanced machine learning initiatives.

• A strong passion for advancing AI infrastructure and cutting-edge model development.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and potential remote work options.

• Collaborative and innovative work environment.