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Temporary Software Engineer Gpu Jobs in Tennessee

... GPU and CPU systems. We need strong engineers with distributed systems background to design and ... You will be responsible for defining and developing software for tasks associated with the ...

... GPU and CPU systems. We need strong engineers with distributed systems background to design and ... Career Level - IC4 As a member of the software engineering division, you will take an active role ...

... GPU and CPU systems. We need strong engineers with distributed systems background to design and ... Career Level - IC4 As a member of the software engineering division, you will take an active role ...

... GPU and CPU systems. We need strong engineers with distributed systems background to design and ... Career Level - IC4 As a member of the software engineering division, you will take an active role ...

... AI and GPU portfolio. The organization partners closely with Engineering, Cloud Platform ... software. * Proven ability to lead multiple concurrent programs while effectively managing ...

... GPU Superclusters. * Partner with engineering, architecture, SRE, network operations, capacity ... Familiarity with network automation technologies, software-defined networking, service reliability ...

Data Engineer

Brentwood, TN · On-site

$70 - $80/hr

Data Engineer LaSalle Network is hiring for a Data Engineer with a client that is focused on ... LaSalle Network is the leading provider of direct hire and temporary staffing services. For over ...

New

... software engineers for the deployment of machine learning models into production environments ... GPU memory optimization techniques (tensor parallelism, pipeline parallelism); LLM caching ...

... software engineers for the deployment of machine learning models into production environments ... GPU memory optimization techniques (tensor parallelism, pipeline parallelism); LLM caching ...

Showing results 21-40

Temporary Software Engineer Gpu information

What are the key skills and qualifications needed to thrive as a temporary software engineer GPU, and why are they important?

To thrive as a Temporary Software Engineer GPU, you need a solid background in computer science, experience with GPU programming (such as CUDA or OpenCL), and proficiency in languages like C++ or Python. Familiarity with GPU development environments, debugging tools, and version control systems, along with any relevant certifications, is highly valuable. Strong problem-solving abilities, adaptability, and effective teamwork skills help set candidates apart in this fast-evolving field. These skills enable efficient development, optimization, and integration of GPU-accelerated applications, which is crucial for meeting project deadlines and technical goals.

What does a temporary software engineer GPU do?

A Temporary Software Engineer GPU is responsible for designing, developing, and optimizing software that interacts with graphics processing units (GPUs), typically for a specific project or short-term period. Their duties may include writing code to improve GPU performance, working on graphics or compute-intensive applications, and collaborating with hardware and software teams to ensure efficient GPU utilization. These roles are often contract-based and require strong programming skills in languages such as C++ or CUDA, as well as a solid understanding of GPU architectures.

What are the typical projects a temporary software engineer GPU might work on, and how do they collaborate with permanent team members?

As a Temporary Software Engineer GPU, you can expect to be assigned to specific, time-bound projects such as optimizing graphics performance, supporting new hardware integration, or debugging GPU-related issues. You’ll often work closely with permanent engineers, participating in code reviews, daily stand-ups, and cross-functional meetings to ensure alignment and knowledge transfer. Collaboration is key, as you may need to quickly get up to speed with existing codebases and tools, and contribute solutions that fit seamlessly into larger, ongoing projects. The role offers a fast-paced environment where adaptability and strong communication skills are highly valued.
What are the most commonly searched types of Software Engineer Gpu jobs in Tennessee? The most popular types of Software Engineer Gpu jobs in Tennessee are:
What cities in Tennessee are hiring for Temporary Software Engineer Gpu jobs? Cities in Tennessee with the most Temporary Software Engineer Gpu job openings:

Principal AI Agent / ML Software Engineer (OCI) (Nashville)

Ll Oefentherapie

Nashville, TN • On-site

$128K - $171K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Job description

Overview

The Principal AI Agent / ML Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud Infrastructure (OCI). This role sets architecture and engineering direction for production-grade agentic AI platforms, autonomous workflows, scalable inference infrastructure, and enterprise AI applications used in large-scale, business-critical environments. The candidate translates ambiguous goals into durable technical strategy, leads multi-team execution, and remains deeply involved in design, code, reviews, operations, and incident follow-up. The role emphasizes distributed systems, AI-native engineering, orchestration of LLMs, tools, APIs, memory, retrieval, evaluation, guardrails, and cloud services, with a focus on reliable, secure, observable, and cost-aware AI platform systems.

Responsibilities
  • Serve as a senior technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
  • Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
  • Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
  • Lead architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
  • Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
  • Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, converting broad goals into executable multi-quarter plans and measurable milestones.
  • Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
  • Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
  • Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
  • Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
  • Mentor Staff and senior engineers, raise architectural standards, and influence engineering practices across OCI without requiring direct management authority.
  • Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.
Required Qualifications
  • Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience.
  • 6-10+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating Senior Staff / Principal-level impact.
  • Proven track record as a Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
  • Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
  • Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
  • Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
  • Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
  • Strong programming skills in Python and ability to contribute high-quality production code, reviews, tests, and debugging in complex distributed environments.
  • Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
  • Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
  • Strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
  • Excellent written and verbal communication, with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.
Preferred Qualifications
  • Experience optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
  • Experience building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.
  • Experience integrating AI systems with enterprise APIs, databases, cloud services, vector databases, embeddings, retrieval systems, identity systems, and policy enforcement layers.
  • Experience with LLM fine-tuning, long-context systems, reasoning models, model routing, caching, batching, quantization, or emerging generative AI research.
  • Experience building evaluation frameworks for agentic systems, including offline evals, online experiments, golden tasks, adversarial testing, regression gates, and observability dashboards.
  • Experience using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar systems in large-scale engineering environments.
  • Track record of defining architectural standards, platform capabilities, or engineering practices adopted across multiple teams or organizations.
  • Experience in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.
Qualifications & Benefits

Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only. US: Hiring Range in USD from: $114,600 to $234,600 per annum. May be eligible for bonus, equity, and compensation deferral.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following: Medical, dental, vision; disability; life insurance; flexible spending accounts; commuter benefits; 401(k) with company match; paid time off; holidays; paid sick leave; parental leave; adoption assistance; employee stock purchase plan; voluntary benefits.

The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.

Required Skills
  • AI Agents
About Us

Oracle brings together data, infrastructure, applications, and expertise to power innovations. We embed AI across our products and services to help customers turn promise into results. We’re committed to growing a workforce that promotes opportunities for all with competitive benefits and flexible options. We also encourage employees to give back through volunteer programs.

We’re committed to including people with disabilities. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or calling 1-888-404-2494 in the United States.

Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veterans’ status, or any other characteristic protected by law. Oracle will consider qualified applicants with arrest and conviction records pursuant to applicable law.

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