MLOps AI Specialist, PyTorch

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

☁️ SaaS

🎯 Recruiter

Human Resources • SaaS • Recruitment

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• Join a leading AI lab's cutting-edge Generative AI team and play a key role in developing next-generation large language models. • Contribute to AI model training and evaluation initiatives by designing, solving, and reviewing advanced machine learning infrastructure and systems challenges. • Your expertise will help improve the quality of training data used to develop frontier AI systems. • Partner with research and engineering teams to identify and address knowledge gaps in MLOps, machine learning infrastructure, and model training systems. • Design challenging, real-world tasks focused on distributed training, ML frameworks, model optimization, and infrastructure engineering. • Develop accurate, well-structured solutions to complex MLOps and ML systems problems. • Evaluate technical tasks and solutions, providing detailed and actionable feedback. • Create evaluation frameworks and scoring rubrics for training pipeline architecture, distributed systems reasoning, performance optimization, and kernel-level programming. • Contribute domain expertise to improve AI model capabilities in machine learning engineering topics. • Collaborate with other subject matter experts to ensure consistency, quality, and technical accuracy across datasets and evaluations.

🎯 Requirements

• 2+ years of professional experience in ML Infrastructure, MLOps, ML Systems Engineering, or a closely related field. • Strong hands-on experience building and operating production-scale machine learning systems. • Advanced proficiency with PyTorch, including model training, optimization, and deployment workflows. • Experience developing, tuning, or optimizing custom GPU kernels using Triton, Pallas, or similar frameworks. • Demonstrated career growth and increasing technical responsibility. • Ability to commit to a full-time, 40-hour-per-week schedule during standard business days. • Excellent written communication skills and the ability to clearly explain complex technical concepts and engineering decisions.