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Opencl Engineer Jobs

2 jobs found

30d ago

Systems Software Engineer

Micron Richardson, TX

Richardson, TX

30d ago Closed

Full time C/c++ Cuda Gpu Computing

This position is no longer accepting applications (closed Nov 3, 2026).

Job Description

Micron’s Systems Software Engineering team is hiring a Principal Systems Software Engineer within the ITP Pathfinding organization’s Storage and Memory Systems (SMS) group. In this role, you will architect, design, and build software that helps validate and communicate the impact of future memory and storage technologies across AI applications, from hardware/software interfaces to inference workflows.

Role Summary

As a Principal Systems Software Engineer, you will enable proof-of-concept hardware capabilities by designing and evolving AI inference software stacks. You will also develop methods to quantify system feature value, lead architecture and development efforts, and contribute to research that identifies memory and storage system challenges and opportunities for AI workloads.

Responsibilities

Design and modify AI inference software stacks to enable proof-of-concept hardware capabilities.
Develop software to quantify and demonstrate the value of proposed system features.
Lead software architecture and development efforts independently and as a technical lead for small teams.
Research emerging AI software topics to identify memory and storage system challenges and opportunities.
Develop and modify Linux applications and libraries using C, C++, Python, Rust, CUDA, and/or SYCL for advanced heterogeneous computing systems.
Develop and use emulators to predict system-level performance and functional impacts before hardware availability.
Debug system-level issues across applications, libraries, operating systems, kernels, system configuration, networks, and hardware/software interfaces.
Use emerging AI tools to improve productivity.
Collaborate across Micron organizations and with external partners.
Mentor interns and earlier-career engineers.
Present technical findings, insights, and innovations to internal or external customers.

Required Qualifications

Bachelor’s or Master’s degree with 10+ years of experience, or a PhD with 7+ years of experience, in Computer Science, Software Engineering, Computer Engineering, or a related field.
Working knowledge of end-to-end AI inference software stack architectures, with hands-on development experience across layers such as frameworks, inference engines, ML compilers, compiler infrastructure, hardware runtimes, or hardware abstraction layers.
Experience debugging issues spanning applications, libraries, operating systems, kernels, networks, and hardware/software interfaces.
Proficient development skills in C, C++, and Python, with Linux-specific programming experience including multithreading, IPC, ioctl, GDB, and interaction with /proc and /sys filesystems.
Experience programming GPUs or other accelerators using CUDA, SYCL, OpenCL, or a comparable programming model.
Demonstrated ability to lead technical initiatives without supervisory authority.
Familiarity with LLM serving internals, including KV-cache management, prefill and decode phases, KV-cache offloading, and disaggregated serving.
Familiarity with inference engines and distributed serving frameworks such as SGLang, vLLM, NVIDIA Dynamo, or TensorRT-LLM.
Strong understanding of heterogeneous compute architecture concepts, including memory hierarchies, NUMA, caching, accelerator architectures, and interconnects such as PCIe, CXL, NVLink, or UALink.

Technologies

C, C++, Python, Rust
CUDA, SYCL, OpenCL
Linux, GDB
/proc, /sys
Multithreading, IPC, ioctl
KV-cache management, prefill and decode phases, KV-cache offloading, disaggregated serving
SGLang, vLLM, NVIDIA Dynamo, TensorRT-LLM
NUMA, PCIe, CXL, NVLink, UALink
Emulators, ML compilers

Preferred Qualifications

Technical leadership experience in a systems-focused pathfinding or research organization.
Technical knowledge of HBM, DRAM, and emerging memory technologies.
Technical knowledge of NVMe SSDs, NAND, and next-generation storage systems.

Location and Experience

Richardson, TX (onsite). Minimum experience: 7 years.

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3mo ago

Senior AI Engineer

Deloitte Cincinnati, OH

Cincinnati, OH

3mo ago Closed

$128k - $253k/yr Full time Senior Apache Airflow Artificial Intelligence

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

Join Deloitte through SFL Scientific as a Senior AI Engineer in Cincinnati, onsite. This role focuses on designing, building, and deploying scalable AI and GenAI infrastructure and data architectures, collaborating with data scientists, machine learning engineers, and industry experts across client engagements. Expect a clear path for professional growth, mentorship, and a culture that emphasizes rigorous engineering practices, modern data platforms, and responsible AI. The position is onsite in Cincinnati, with a salary range of USD 128,000 to 252,500 per year.

Responsibilities

Collaborate with clients to architect, build, and deploy new systems that enable machine learning and automation initiatives.
Apply advanced skills in modern data architecture, data engineering for science, data transformation, and management of structured and unstructured data across cloud and on premise environments.
Design and guide the development of scalable, high performance data architecture solutions that support business needs and AI/GenAI use cases.
Enhance data architectures and pipelines; define schemas across graph, SQL, and NoSQL databases to enable scalable algorithms aligned with agile priorities.
Contribute to architecture and deployment discussions to ensure solutions are scalable, secure, and highly available in cloud or on prem.
Implement engineering best practices in automation, high performance computing, and AI/GenAI infrastructure design.
Define and drive technology proof of concepts to validate new data and cloud solutions.
Demonstrate thought leadership and practical execution in advancing modern data architecture and technology modernization.
Mentor and guide junior teammates in engineering best practices and professional growth.

Requirements

Bachelor's degree in a STEM field or equivalent experience.
4+ years in data engineering, data science, software engineering, or MLOps with a focus on deploying AI and machine learning.
4+ years designing cloud solutions and supporting production projects with hands-on work in AWS (or Azure, GCP equivalents).
4+ years programming with Linux shell/CLI, Python, SQL, PowerShell.
2+ years leading technical delivery teams on complex projects.
2+ years in DevOps and CI/CD tools such as Puppet, Ansible, Chef, Airflow, Terraform, Jenkins.
2+ years building databases and ETL/ELT pipelines across relational, NoSQL, and graph databases like Neo4j.
2+ years deploying and optimizing Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, and related technologies.
Located within commuting distance to a Deloitte consulting office and able to travel about 10% as needed.
Limited immigration sponsorship may be available.

Technologies

Python
SQL
Linux Shell/CLI
PowerShell
Puppet
Ansible
Chef
Airflow
Terraform
Jenkins
Kubernetes
Docker
NVIDIA TensorRT
Triton
RAPIDs
Kubeflow
MLflow
Kafka
Graph databases
Neo4j
NoSQL
AWS
Azure
GCP
CUDA
OpenCL

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