Top Tech Jobs & Startup Jobs

Support data center acquisition by sourcing colocation, powered shell, land+power, and expansion opportunities; conduct outreach to brokers and owners; build and manage a CRM pipeline; perform market screening and early diligence; validate provider claims; organize diligence materials; track deal stages, MW capacity, timelines, and risks; and improve sourcing workflows and qualification frameworks.

Develop, optimize, and validate high-performance ML and linear-algebra kernels for Cerebras wafer-scale hardware. Implement low-level assembly and a C-like DSL (CSL), model and analyze performance, build testing methodologies, and collaborate with chip and system architects to maximize compute utilization for state-of-the-art AI and HPC workloads.

Design, implement, optimize, and validate high-performance ML and linear algebra kernels for Cerebras hardware. Develop low-level assembly and CSL routines, use mathematical performance models, create unit/system tests, and collaborate with chip and system architects to maximize compute utilization and scale kernels for state-of-the-art AI/HPC workloads.

Design and implement high-performance distributed runtime components for large-scale training and inference. Optimize data and communication pipelines, enable scalable multi-node execution, collaborate with ML and compiler teams, diagnose performance issues via profiling, and contribute to system architecture and roadmap for cutting-edge AI workloads.

Lead and build a research-focused ML team to develop and adapt advanced ML algorithms (post-training, RL, pretraining, sparsity, dataset curation) for deployment on Cerebras hardware, collaborate across teams and external partners, and guide production training, tuning, and evaluation to drive hardware-software co-design and performance optimization.

Lead and grow a Bengaluru engineering team building AI-native developer productivity and infrastructure. Own CI/CD, build/test performance, developer observability, environments, automation, and AI-assisted workflows. Mentor engineers, set technical direction, run incident response, and partner across orgs to measurably improve engineering velocity, reliability, and developer experience.

Lead corporate FP&A for a newly public AI hardware company: build planning, forecasting, reporting, KPI dashboards, revenue forecasting, G&A business partnering, and automation to deliver investor-grade insights and scalable finance operations.

Bring up state-of-the-art open-source or proprietary LLMs on Cerebras CSX systems across the full stack: model translation, graph lowering, compiler optimizations, runtime integration, performance tuning, debugging, and prototyping tooling improvements to accelerate future bring-ups.

Build and maintain CI/CD pipelines and artifact lifecycle systems, provision and optimize cloud (AWS) CI infrastructure, troubleshoot build and pipeline issues, improve developer tooling and build/test infrastructure, support code review/workflow improvements, participate in on-call incident response, and contribute to AI tooling to boost engineering productivity.

Lead owners technical oversight for mechanical infrastructure in leased AI data centers: review designs, approve equipment, validate high-density cooling architectures, support construction, commissioning, operational readiness, and cross-functional coordination to ensure performance and reliability.