Senior MLOps Engineer, Large Language Models (Remote, India)

About The Company

Para AI Labs is a premier AI research and development organization dedicated to advancing the frontiers of artificial intelligence technology. Our mission is to develop innovative solutions that push the boundaries of what is possible with machine learning and AI systems. We collaborate with leading industry partners, research institutions, and top-tier AI talent worldwide to create impactful AI models and infrastructure. At Para AI Labs, we foster a culture of innovation, technical excellence, and continuous learning, ensuring our team remains at the cutting edge of AI research and deployment.

About The Role

We are seeking experienced MLOps Engineers to join our team remotely from India. This role focuses on designing and implementing complex tasks related to machine learning infrastructure, systems, and operations, specifically for training large language models. As part of the GenAI team at a leading frontier AI lab, you will play a critical role in shaping the technical challenges that influence how next-generation models reason about MLOps and ML systems. Your work will involve developing reference solutions, creating evaluation rubrics, and collaborating with cross-functional teams to ensure the robustness and efficiency of training pipelines. This is an exciting opportunity to contribute directly to groundbreaking AI research and development efforts, working alongside some of the brightest minds in the field.

Qualifications

The ideal candidate will possess a minimum of two years of professional experience in ML Infrastructure, MLOps, or ML Systems Engineering within recognized, top-tier organizations. You should have hands-on experience working with JAX and/or PyTorch at scale in production environments, demonstrating your ability to handle real training workloads. Experience in writing or optimizing custom GPU kernels using Pallas (JAX) or Triton is essential. A proven track record of career progression, excellent problem-solving skills, and the ability to communicate complex technical concepts clearly in written English are also required. Additionally, reliable availability for at least 30 hours per week during weekdays is necessary to ensure seamless collaboration with the team.

Responsibilities

Your primary responsibilities will include designing challenging tasks related to MLOps, ML infrastructure, and systems for model training. You will develop accurate and well-structured reference solutions that cover distributed training, training pipelines, and GPU kernel optimization. Evaluating submissions from other engineers and providing clear, constructive technical feedback will be a key part of your role. You will also develop rubrics and guidelines to assess training pipeline design, distributed systems reasoning, and kernel-level performance optimization. Collaboration with other ML subject matter experts will ensure consistency and accuracy across training data and methodologies. Moreover, you will guide research and engineering teams in closing knowledge gaps related to ML framework internals, fostering a culture of continuous improvement and innovation.

Benefits

This role offers competitive USD rates for remote MLOps work based in India, with compensation ranging from $35 to $45 per hour. You will enjoy the flexibility of working fully remotely from anywhere in India, with a commitment of 30 to 40 hours per week on weekdays. Employment is secured through W-2 via Cincinnatus LLC, providing stability and ease of payroll management. Working at Para AI Labs allows you to make a tangible impact on cutting-edge AI models, contributing to projects that shape the future of AI technology. You will have the opportunity to collaborate with senior ML engineers and researchers from around the world, gaining valuable insights and expanding your professional network. The position offers a structured environment with clear deliverables, ensuring your work is recognized and valued.

Equal Opportunity

Para AI Labs is committed to creating an inclusive and diverse work environment. We are an equal opportunity employer and do not discriminate based on race, ethnicity, gender, sexual orientation, age, disability, or any other protected characteristic. We believe that diverse teams foster innovation and creativity, and we encourage candidates from all backgrounds to apply. Our hiring process is transparent, fair, and designed to select the best talent based on merit and potential.