The MLOps Engineer role focuses on transforming language models into real-world applications for a global audience.
The position involves building applications that enable significant real-world impact and high usage.
This is a global role with a hybrid work arrangement, combining flexible remote work with in-office collaboration at the company's headquarters.
The engineer will work closely with regional teams across product, engineering, operations, infrastructure, and data to build and scale impactful AI solutions.
Responsibilities include fine-tuning state-of-the-art models, designing evaluation frameworks, and bringing AI features into production.
The engineer's work ensures that models are intelligent, safe, trustworthy, and impactful at scale.
Key tasks include running and managing open-source models efficiently, ensuring high performance and stability across GPU, CPU, and memory resources, monitoring and troubleshooting model inference, and collaborating with engineers to implement scalable and reliable model serving solutions.
Requirements:
Candidates must have experience with model serving platforms such as vLLM or HuggingFace TGI.
Proficiency in GPU orchestration using tools like Kubernetes, Ray, Modal, RunPod, or LambdaLabs is required.
The ability to monitor latency, costs, and scale systems efficiently with traffic demands is essential.
Experience in setting up inference endpoints for backend engineers is necessary.
Benefits:
The position offers a flat structure and real ownership within the team.
Employees will have full involvement in direction and consensus decision-making.
There is flexibility in work arrangements.
The role is high-impact with visibility across product, data, and engineering teams.
Compensation is top-of-market with performance-based bonuses.
Employees will gain global exposure to product development.
Additional perks include housing rental subsidies, a quality company cafeteria, and overtime meals.
Health, dental, and vision insurance are provided.
Global travel insurance is available for employees and their dependents.