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Temporary Nvidia Engineering Jobs in Kentucky (NOW HIRING)

$65 - $90/hr

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS ... This is a temporary role with the potential to convert to full‑time employment. What You Will Do

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Temporary Nvidia Engineering information

What is a temporary Nvidia engineering role?

Temporary Nvidia Engineering jobs are short-term positions at Nvidia, typically filled to meet project demands, cover employee absences, or provide specialized skills for a limited period. These roles can range from hardware and software engineering to research and development positions. Temporary engineers work on innovative projects involving graphics processing, AI, and other cutting-edge technologies. Although these jobs are not permanent, they provide valuable experience and networking opportunities within a leading tech company like Nvidia.

What types of projects do temporary Nvidia engineers typically work on, and how do they collaborate with full-time teams?

Temporary Nvidia Engineering roles often focus on short-term, high-priority projects such as software development, hardware validation, or performance optimization. Contractors are usually integrated into existing teams and work closely with full-time engineers, project managers, and cross-functional partners to meet project milestones. While the assignments are time-bound, temporary engineers are expected to contribute actively during team meetings, participate in code reviews, and share updates regularly. This collaborative environment helps ensure project continuity and gives temporary staff valuable exposure to Nvidia’s cutting-edge technologies and workflows.

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

To thrive as a Temporary Nvidia Engineer, you need a solid background in computer engineering, programming (C/C++ or Python), and experience with hardware or software development, often supported by a relevant degree. Familiarity with Nvidia’s development tools such as CUDA, GPU architecture, and version control systems is typically required. Strong problem-solving skills, adaptability, and effective communication help you quickly integrate with teams and adapt to project needs. These skills ensure high productivity and quality contributions in a fast-paced, innovation-driven environment where contract roles demand rapid impact.

What is the difference between Temporary Nvidia Engineering vs Temporary Nvidia Data Scientist?

AspectTemporary Nvidia EngineeringTemporary Nvidia Data Scientist
Required CredentialsBachelor's or Master's in Engineering, Computer Science, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentHardware development, software engineering, system testingData analysis, model development, statistical analysis
Employer & Industry UsageUsed in hardware and software product development within NvidiaUsed in AI, machine learning projects, and data-driven solutions at Nvidia

Temporary Nvidia Engineering focuses on hardware and software development, requiring engineering credentials and working in product development environments. In contrast, Temporary Nvidia Data Scientist emphasizes data analysis and modeling skills, working primarily on AI and machine learning projects. Both roles are essential in Nvidia's innovation pipeline but differ in their technical focus and daily tasks.

What are the most commonly searched types of Nvidia Engineering jobs in Kentucky?

The most popular types of Nvidia Engineering jobs in Kentucky are:

What are popular job titles related to Temporary Nvidia Engineering jobs in Kentucky?

For Temporary Nvidia Engineering jobs in Kentucky, the most frequently searched job titles are:

What job categories do people searching Temporary Nvidia Engineering jobs in Kentucky look for?

The top searched job categories for Temporary Nvidia Engineering jobs in Kentucky are:

Infographic showing various Temporary Nvidia Engineering job openings in Kentucky as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 65% In-person, 11% Hybrid, and 24% Remote job distribution.

Advanced Innovation Manufacturing Engineer, Contingent Worker

WillHire

Georgetown, KY • On-site

$69 - $94/hr

Other

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Magnit Direct Sourcing on behalf of Toyota is currently hiring an Advanced Innovation Manufacturing Engineer for a temporary assignment in Georgetown, Kentucky.

This is a 12-month contract. The pay range for this role is between $50.00- $68.00/Hr. Benefits: Medical, Dental, Vision, 401K.

DescriptionModel Development & Training Speed
  • Design and implement computer vision models for defect detection, segmentation, and classification.
  • Accelerate training cycles using synthetic data, active learning, and domain randomization to cover rare defects and specification variance.
Production Deployment
  • Package models and services using Docker and manage deployments through Kubernetes or equivalent orchestration tools.
  • Implement version control, rollback strategies, and observability for latency, drift, and false-positive/false-negative metrics.
Edge Optimization
  • Optimize inference for edge and embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) to meet strict real-time latency requirements for moving-line inspection.
  • Ensure consistent performance under varying lighting, optics, and surface conditions.
Integration with Manufacturing Systems
  • Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.
  • Align deployments with IC S+, GALC, and TVIP architecture standards for plant-level connectivity and reliability.
Data Strategy & Quality Control
  • Lead data collection campaigns, manage annotation workflows, and establish quality gates for model validation.
  • Utilize synthetic data pipelines and augmentation techniques to improve model robustness and reduce training time.
Reliability & Sustainment
  • Ensure uptime and availability targets are met through proactive monitoring, calibration (MSA), and backup/restore processes.
  • Implement drift detection, audit false-out risks, and perform root cause analysis for inspection failures.

Reporting to the Manufacturing InnovationManager, the person in this role will support the Production Engineering objectiveto improve manufacturing competitiveness.

Key Responsibilities
  • Develop and deploy production-grade machine learning models for industrial vision inspection systems across manufacturing lines.
  • Accelerating model development and training using advanced techniques such as synthetic data generation, ensuring high accuracy and generalization, and delivering containerized software optimized for edge hardware
  • Development of new technologies for PE and Manufacturing competitiveness improvement
  • Lead and manage projects from concept to launch for new technology first introduction to manufacturing including creating schedules, establishing punch lists, and meeting established due dates and milestones.
  • Search for innovative solutions, test them in a manufacturing setting, and develop business case justification to gain approval to purchase if trials prove successful.
  • Close collaboration between both internal and external groupsto ensurequalityandto integrate robust AI solutions into high-volume manufacturing environments.
Qualifications
  • Ability to travel to all North American Manufacturing Centers along with Canada, MexicoandJapan
  • Experience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates (Y/N – text follow up)
  • Bachelor’sdegree inElectrical Engineering, Mechanical Engineering,Computer Science, InformationTechnologyor related field.
  • 2+( 5preferred)years of experience in industrial machine vision and edge AI deployment.
  • Proficiencyin Python and C++ with strong knowledge of ML frameworks (PyTorch, TensorFlow).
  • Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
  • Familiarity with ONNX Runtime,TensorRT, and optimization for embedded hardware.
  • Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT).
  • Experience managing the full model lifecycle: data collection, labeling, validation, rollout, monitoring, and retraining
  • Experience in areas such as object detection, classification, segmentation and familiarity with mainstream object detection and semantic/instance segmentation models
  • Familiarity with industrial cameras, lighting, and optics, including trigger-based image capture
  • Experience balancing inspection accuracy with false positives vs flow-out risk in quality-critical applications
Education/Experience
  • Master’s Degree in Engineering or AdvancedDegreein related fields
  • 2-5 years of experience.
  • Academic research experience innew technology
  • Project management work involving internal and external parties – 6 monthsor greater
  • Experience deploying equipment includingestablishingRJ,PFMEA, andqualitycontrol plan
  • Experience deployingautomotive production equipment
  • Experience in Robotics to include operation, teaching,maintenance,and safety
  • Expertise insynthetic data generation techniques (GANs, VAEs,NeRFs, Blender) and domain randomization for model generalization.
  • Experience with high-speed inline inspection systems and vision-based process control.
  • Knowledge ofIIoTdata pipelines and messaging standards.
  • Strong understanding of calibration, measurement system analysis (MSA), and quality-critical inspection requirements.
Added Bonus
  • Ability to deliver production-ready AI solutions under strict timelines.
  • Strong problem-solving and cross-functional collaboration skills.
  • Commitment to quality, reliability, and continuous improvement in manufacturing environments

Magnit Direct Source does not offer support or sponsorship of job applicants for employment-based visas or any other work authorization for this role now or in the future. You must have the right to work in the United States and not require Magnit Direct Source support or sponsorship for immigration-related employment (e.g., H-1B, O-1, E-3, H-1B1, TN, F-1 OPT, F-1 STEM OPT, F-1 CPT, ‘job flexibility benefits’ [also known as I-140 or Adjustment of Status portability], etc.) now or in the future. You should not apply for this role if you will require Magnit Direct Source to assist with immigration support or sponsorship now or in the future.

Magnit is an equal opportunity employer, and all applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.

Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.

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