job description
Join ByteDance as a Product Solution Architect for ModelArk, our cutting-edge Model-as-a-Service (MaaS) platform on BytePlus. ModelArk empowers businesses with secure, scalable, and cost-effective AI solutions, including model inference, evaluation, and deployment. In this role, youâll bridge the gap between technical innovation and business needs, designing architectures that drive adoption of our MaaS offerings.
Based in Bali, youâll collaborate with cross-functional teams to shape the future of AI-driven products, ensuring seamless integration, performance optimization, and customer success. This is a unique opportunity to work at the intersection of cloud computing, machine learning, and enterprise solutions in one of the worldâs most dynamic tech ecosystems.
ByteDance offers a fast-paced, innovative environment where your expertise will directly impact global AI infrastructure. If youâre passionate about transforming complex technical challenges into scalable solutions, weâd love to hear from you.
Responsibility
- Design and architect scalable, high-performance MaaS solutions tailored to client needs, leveraging ModelArkâs capabilities.
- Collaborate with product, engineering, and sales teams to define technical roadmaps and go-to-market strategies.
- Develop proof-of-concepts (PoCs) and demos to showcase ModelArkâs value proposition to enterprise clients.
- Optimize model inference pipelines for latency, cost, and accuracy, ensuring seamless deployment at scale.
- Provide technical guidance to customers and internal stakeholders on best practices for MaaS adoption.
- Identify and address performance bottlenecks in AI/ML workflows, proposing innovative solutions.
- Stay ahead of emerging trends in MLOps, cloud AI, and model serving to drive continuous platform improvements.
- Document architectural decisions, APIs, and integration guidelines for internal and external use.
Qualifications
- 5+ years of experience in solution architecture, cloud computing, or AI/ML infrastructure, with a focus on production-grade systems.
- Deep understanding of machine learning models, inference optimization, and MLOps pipelines.
- Hands-on experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Proficiency in Python, Go, or Java and familiarity with ML frameworks (TensorFlow, PyTorch).
- Strong problem-solving skills and ability to translate business requirements into technical specifications.
- Experience with API design, microservices, and distributed systems at scale.
- Excellent communication and stakeholder management skills to align technical and business goals.
- Bachelorâs or Masterâs degree in Computer Science, Engineering, or a related field (or equivalent experience).