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About the Role

Nscale is seeking Senior / Staff AI Engineers to join its core AI team and develop the systems powering its GenAI cloud platform. This role focuses on designing and optimizing distributed systems for large-scale AI tasks, including training, post-training, evaluation, and inference, under strict performance and efficiency constraints. It's a hands-on position for engineers aiming to advance AI system development, optimization, and consumption.

Responsibilities

Design, build, and optimize scalable AI platform systems.
Drive inference performance and efficiency, including KV cache management, continuous batching, speculative decoding, and quantization.
Build and improve post-training services, including fine-tuning (LoRA, QLoRA, adapters, full fine-tuning) and alignment (RLHF, DPO, reward modelling).
Develop dataset curation and data processing workflows.
Develop evaluation and benchmarking systems to measure model quality, safety, regression, system performance, and real-world behavior.
Develop and optimize distributed systems for GPU/accelerator workloads, focusing on scalability, reliability, and efficiency.
Conduct performance analysis and bottleneck investigations across multiple components and stacks.
Collaborate with research, infrastructure, and product teams to build platform components based on customer demand and industry direction.
Build developer-facing APIs, SDKs, and tooling for Nscale’s AI services.

Requirements

5+ years of experience building production systems in machine learning, distributed systems, or high-performance infrastructure.
4+ years of hands-on experience in at least one core area within large-scale, production AI environments (e.g., AI labs, hyperscalers), such as inference optimization, large-scale training/pre-training systems, post-training, or evaluation and benchmarking frameworks.
Strong hands-on expertise in at least one core area, with working knowledge across others.
Proven ability to design, optimize, and operate systems at scale, with a strong understanding of performance trade-offs.
Deep understanding of transformer architectures, LLMs, and/or multimodal models.
Strong proficiency in Python and PyTorch, with a track record of building production-grade ML systems.
Experience with distributed compute and training paradigms (e.g., data/model parallelism, sharding, scheduling).
Experience working close to the hardware/software boundary, such as GPU/accelerator optimization or memory management.
Experience building or operating production inference or training systems at scale.
Ability to design clean abstractions, APIs, and reusable systems for other engineers.
Strong engineering fundamentals, with a track record of writing maintainable, well-tested, production-quality code.

Skills

Python
PyTorch
Machine Learning
Distributed Systems
High-Performance Infrastructure
Inference Optimization
Large-Scale Training
Post-Training (Fine-tuning, Alignment, Distillation)
Evaluation and Benchmarking Frameworks
Transformer Architectures
LLMs
Multimodal Models
Distributed Compute
Training Paradigms
GPU/Accelerator Optimization
CUDA
ROCm
Memory Management
System-Level Performance Tuning
API Design
OpenAPI 3.0+

Experience Level

Senior
Staff

About the Company

Nscale is building a vertically integrated GenAI cloud platform, owning data centers, software, and applications for the AI stack using sustainable technology.
The company culture emphasizes relentless innovation, ownership, accountability, pride in work, excellence, urgency, openness, transparency, inspiration, collaboration, swiftness, respect, adaptability, and resilience.

Equal Opportunity

Nscale is committed to fostering an inclusive, diverse, and equitable workplace.
The company encourages applications from candidates of all backgrounds, experiences, and abilities, including people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.
Nscale will provide accommodations for specific situations upon request.