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Senior Staff Data Engineer
Biohub
NY · Redwood City, CA
- $270,000 to $300,000 USD / year
As a Senior Staff Data Engineer at Biohub, you'll be designing systems that ingest data from public repositories, transform heterogeneous biological formats into AI-ready datasets, combine…
Added 2 hours ago
FT
Principal Quant Developer
Fidelity Technology Group, LLC
Boston, MA
- $107,000 to $216,000 USD / year
Operationalizing ML models and pipelines on AWS using modern MLOps principles, including SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access,…
Added 8 hours ago
Software Program Manager
USU RESEARCH FOUNDATION
DENVER, CO
…delivery forecasts, resource allocation, risks, and impediments to senior leadership and customers Required Qualifications: - Bachelor's degree in technical engineering, computer science,…
Added 2 days ago
Senior Data Scientist - LLMs for Fraud Detection
DataVisor
Mountain View, CA
LLMs and large models: fine-tuning, post-training, or building and training large models in production or serious research, or
Added 2 days ago
Principal Software Engineer, AI Defense (Hybrid)
Cisco Systems, Inc.
Milpitas, CA
As a Principal Software Engineer for AI Defense, you will serve as the chief technical authority driving the end-to-end security architecture for Cisco's enterprise AI ecosystems. You will…
Added 2 days ago
Machine Learning Research Engineer
Apple
Seattle, WA
The Human and Object Understanding team (HOUr) in the Intelligent System Experience (ISE) organization is looking for Research Engineers with a strong foundation in Machine Learning and…
Added 3 days ago
AI Red Team Lead Engineer
U.S. Bank
Irving, TX
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Added 3 days ago
ML Innovation for Products, PhD Research Intern
Meta
Menlo Park, CA · Sunnyvale, CA
The ML Innovation for Products (MLIP) team is an applied machine learning and research team within Meta's Ranking & Foundational AI org, focused on the state-of-the-art (SOTA) 0-to-1 ML…
Added 3 days ago
AI Engineer 4 (MLX)
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New York, NY
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Added 3 days ago
Senior Cloud Engineer, Information Technology [R0150849]
University of Nevada, Las Vegas
United States
The University of Nevada, Las Vegas invites applications for Senior Cloud Engineer, Information Technology [R0150849].
Added 3 days ago
SO
Senior AI Engineer
State of Massachusetts
Boston, MA
- $89,993.11 USD / year
…****(Commensurate with experience)** GENERAL STATEMENT OF DUTIES: The Senior AI Engineer designs the architecture for, builds, and deploys AI-enabled applications in OSA's Microsoft GCC…
Added 3 days ago
Morningstar Development Program (MDP): Associate Software Engineer (Central Tech AI)
MstarInc Morningstar Inc. Legal Entity
United States
Engage in training and development sessions across Morningstar to build a strong foundation for a long-term career in technology and AI.
Added 3 days ago
Associate Software Engineer (Central Tech AI) - Partner Link
MstarInc Morningstar Inc. Legal Entity
United States
Engage in training and development sessions across Morningstar to build a strong foundation for a long-term career in technology and AI.
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Lead Machine Learning Engineer , AI Defense (Hybrid)
Cisco Systems, Inc.
Milpitas, CA
Cisco’s AI Defense is dedicated to securing the next generation of enterprise AI platforms, autonomous agents, and foundation models. Our team brings together world-class distributed…
Added 4 days ago
Network Engineer
North Dakota University System
ND
Position Title: Network Engineer (Associate, Regular, or Senior)
Added 4 days ago
M
Senior AI Engineer
MassCareers
MA
- $89,993.11 USD / year
The Senior AI Engineer designs the architecture for, builds, and deploys AI-enabled applications in OSA's Microsoft GCC environment. Working with the Innovation Assistant Director and Cloud…
Added 4 days ago
Senior Network Engineer
Florida Polytechnic University
United States
The Senior Network Engineer serves as a member of the IT Infrastructure team, reporting to the Director of IT Infrastructure Services and working with the Lead Network Engineer. This role…
Added 4 days ago
Sr Machine Learning Engineer
Disney Entertainment & Sports LLC
Santa Monica, CA
As a Senior Machine Learning Engineer, you will be expected to lead search algorithm research, development, and productionization for existing and new product areas. You will identify…
Added 4 days ago
Staff/Sr. ML Infrastructure Engineer, Foundation Model Compute Infra
Apple
Cupertino, CA
As a Senior/Staff Engineer on the Foundation Model Compute Infrastructure team, you will design and build large-scale infrastructure that powers foundation model training, fine-tuning,…
Added 4 days ago
Senior AI/ML Research Engineer, Cloud AI Research and AI Rapid Response
Google
Mountain View, CA
Share Senior AI/ML Research Engineer, Cloud AI Research and AI Rapid Response
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Staff/Sr. ML Infrastructure Engineer, Foundation Model Compute Infra
Apple
Santa Clara, CA
As a Senior/Staff Engineer on the Foundation Model Compute Infrastructure team, you will design and build large-scale infrastructure that powers foundation model training, fine-tuning,…
Added 5 days ago
Forward Deployed AI Engineer
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Los Angeles, CA · NY
…datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM…
Added 5 days ago
Senior Forward Deployed Software Engineer - Equities Technology
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Miami · New York
…and quantitative finance. Its mission is to accelerate the research and trading strategies of Millennium’s systematic Portfolio Management teams by serving as an internal center of…
Added 5 days ago
AI Engineer 4 (Gen AI Platform Services: Agentic Systems)
Capital One
San Francisco, CA · McLean, VA · Cambridge, MA · San Jose, CA · NY
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search,…
Added 5 days ago
AI Engineer 4 (MLX, Agentic AI, Gen AI workflows, GraphRAG)
Capital One
NY · San Francisco, CA · McLean, VA · Cambridge, MA · San Jose, CA
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search,…

Cerebras Systems

Senior Software Engineer, ML API – AI Inference

Sunnyvale, CA, United States

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Job details

Experience: 5+ years of software engineering experience, including independent ownership of production services, distributed systems, or substantial software components.
Posting language: English
Posted: Oct 27, 2026

Original job description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About the Role

Cerebras is building a new generation of disaggregated AI inference systems that combine GPU-accelerated prefill with ultra-fast decode on the Cerebras Wafer-Scale Engine.

We are hiring a Senior Software Engineer to build and evolve the ML API layer that makes this heterogeneous serving system accessible, reliable, and easy to use. You will own significant features and components across our inference APIs, model integration layer, and request-routing services, delivering a consistent experience across models and accelerator backends.

This role sits at the intersection of machine learning systems, API design, model serving, and distributed systems. You will translate evolving model capabilities and customer requirements into clear designs, lead implementation across multiple components, and carry features through validation, rollout, and production operation. Your work will help ensure that streaming, sampling, tool use, structured outputs, multimodal inputs, and model configuration behave correctly and consistently.

You will work closely with model enablement, compiler, runtime, cloud infrastructure, product, and customer-facing teams, as well as customers directly. This is a hands-on individual-contributor role with opportunities to lead small project teams, mentor engineers, and improve the quality and reliability of production inference software.

Responsibilities

Own features end to end. Design, implement, test, and operate features for chat completions, text generation, streaming, model configuration, tool calling, structured outputs, multimodal inputs, and emerging inference capabilities.
Lead multi-component delivery. Write clear design documents, evaluate technical tradeoffs, break projects into deliverable milestones, and coordinate implementation with a small group of engineers and partner teams.
Deliver consistent API behavior. Implement clear request and response semantics across GPU prefill, Cerebras decode, and other inference backends. Maintain compatibility with widely adopted inference interfaces and evolve owned APIs through validation, versioning, and deprecation best practices.
Enable new models and capabilities. Integrate foundation models, tokenizers, chat templates, generation configuration, sampling methods, and model-specific features into the serving platform.
Integrate serving components. Extend inference services and their integration with frameworks and runtimes such as vLLM, PyTorch, Hugging Face libraries, LLGuidance, and Cerebras runtime components.
Support disaggregated inference. Implement routing, state-transfer integration, error handling, retries, cancellation, and request lifecycle management to coordinate GPU prefill with Cerebras decode.
Deliver measurable performance improvements. Diagnose bottlenecks and improve time to first token, streaming latency, throughput, and resource efficiency through changes to tokenization, serialization, batching, scheduling, and communication.
Own correctness and release quality. Build conformance tests, model-validation suites, numerical comparisons, integration tests, and performance benchmarks that catch regressions in owned features and support safe releases.
Strengthen production reliability. Improve service metrics, tracing, logging, alerts, and diagnostic tools. Investigate production incidents, resolve root causes, and follow through on improvements to resilience and incident response.
Improve customer and developer experience. Partner with product, support, and solutions teams to understand user needs and make practical tradeoffs. Improve configuration, documentation, examples, and debugging workflows.
Raise the engineering quality bar. Provide thoughtful design and code reviews, mentor less-experienced engineers, share domain knowledge, and proactively remove delivery roadblocks.

Minimum Qualifications

5+ years of software engineering experience, including independent ownership of production services, distributed systems, or substantial software components.
Strong programming ability in Python and proficiency in Go, C++, Rust, or another language used to build production services.
Experience designing and delivering features that span multiple components, including documenting designs, evaluating tradeoffs, and coordinating implementation with other engineers.
Experience building and evolving production APIs, with sound practices for validation, error handling, compatibility, and testing. Familiarity with REST, gRPC, or streaming protocols.
Experience integrating software across service, framework, runtime, or infrastructure boundaries.
Experience operating services on Linux using containers, Kubernetes or comparable orchestration systems, and CI/CD.
Ability to diagnose correctness, reliability, and performance issues across distributed components and deliver measurable improvements.
Strong communication and collaboration skills, including experience leading technical delivery for a small project and supporting other engineers through reviews or mentorship.
Ability to turn ambiguous requirements into maintainable software while balancing customer needs, delivery timelines, and operational quality.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline, or equivalent practical experience.

Preferred Qualifications

Experience building or operating production ML or LLM inference APIs, including OpenAI-compatible interfaces.
Experience extending or contributing to vLLM, SGLang, PyTorch, Hugging Face Transformers, Triton, TensorRT-LLM, or another ML systems project.
Understanding of tokenization, chat templates, generation configuration, logits processing, stopping criteria, tool calling, structured generation, or constrained decoding.
Experience with disaggregated prefill/decode architectures, KV-cache transfer, prefix caching, chunked prefill, or inference request scheduling.
Experience building API conformance, model-quality, numerical-comparison, determinism, or performance-regression test systems.
Experience with multi-model or multi-tenant serving, including routing, admission control, quotas, rate limiting, or capacity-aware scheduling.
Experience developing performance-sensitive or highly concurrent services in Go, C++, Rust, or a similar language.
Familiarity with GPU inference, AMD Instinct accelerators, ROCm, CUDA, collective communication, or multi-node model serving.
Familiarity with reduced-precision inference and quantization formats such as BF16, FP8, FP4, INT8, or INT4.
Experience building SDKs, developer tools, configuration systems, or self-service ML workflows, or collaborating directly with customers and open-source communities.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

Build a breakthrough AI platform beyond the constraints of the GPU.
Publish and open source their cutting-edge AI research.
Work on one of the fastest AI supercomputers in the world.
Enjoy job stability with startup vitality.
Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here https://www.cerebras.net/privacy/ to review our CCPA disclosure notice.

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More about this job

Skills

ML
Machine learning
API development
PyTorch
Hugging Face
Scheduling
Communication skills
Incident response
Documentation
Debugging
Python
Go
C++
Rust
Linux
Kubernetes
CI/CD
Collaboration
Computer science
Computer engineering
Electrical engineering

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