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Junior Nvidia Engineering Jobs in Georgia (NOW HIRING)

Sr Advanced AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Data Engineering * Partner with Data Engineering teams on ETL workflows and data preparation for ... Lead proof-of-concept initiatives and mentor junior engineers through early-stage experimentation.

... g., NVIDIA Jetson platforms, SDRs) * Architect and optimize systems for embedded and HPC ... Collaborate cross-functionally with engineering, product, and business teams to deliver robust and ...

... g., NVIDIA Jetson platforms, SDRs) * Architect and optimize systems for embedded and HPC ... Collaborate cross-functionally with engineering, product, and business teams to deliver robust and ...

Sr Advanced AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

You will collaborate crossfunctionally, mentor junior engineers, and influence multiple projects ... Experience deploying AI/ML solutions on edge devices (e.g., NVIDIA Jetson) is a plus but not ...

... NVIDIA GPU platforms, cooling strategies, and automated data center workflows. * Mentor Teams: Create training documentation and provide technical guidance to junior engineers to scale operational ...

Sr Advanced AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

You will collaborate crossfunctionally, mentor junior engineers, and influence multiple projects ... Experience deploying AI/ML solutions on edge devices (e.g., NVIDIA Jetson) is a plus but not ...

... engineers, platform engineers, data scientists and many more, enabling you to level up in true end ... Provide guidance to junior team members on model development and EDA * Work with Product Manager(s ...

Junior Nvidia Engineering information

What is a junior Nvidia engineer?

A Junior Nvidia Engineer is an early-career professional who works with Nvidia technologies, such as GPUs, AI hardware, and related software development kits. Their responsibilities typically include assisting in the design, development, testing, and optimization of software or hardware solutions utilizing Nvidia platforms. They often collaborate with senior engineers to solve technical challenges, support product development, and learn about advanced computing technologies. This role is ideal for those interested in graphics processing, machine learning, and high-performance computing. Junior Nvidia Engineers usually have a background in computer science, electrical engineering, or a related field.

What are the key skills and qualifications needed to thrive as a junior Nvidia engineer?

To thrive as a Junior Nvidia Engineer, you need a solid grounding in computer science principles, programming (especially in C++ and Python), and a relevant degree such as Computer Engineering or Electrical Engineering. Familiarity with Nvidia's CUDA platform, GPU architectures, and common development tools like Git and Linux is typically required. Strong problem-solving skills, effective teamwork, and a willingness to learn new technologies are crucial soft skills in this role. These abilities are essential to contribute to innovative hardware and software solutions, collaborate effectively, and adapt to the rapid advancements in GPU technology.

What are some common challenges faced by junior engineers at Nvidia, and how can they overcome them?

As a junior engineer at Nvidia, you may encounter challenges such as adapting to a fast-paced environment, learning proprietary technologies, and collaborating with cross-functional teams. It's common to feel overwhelmed by the complexity of projects and the high expectations for innovation. To overcome these hurdles, proactively seek mentorship from experienced colleagues, participate in internal training sessions, and regularly communicate with your team to clarify goals and expectations. Building strong technical foundations and asking questions when you need support can help you grow quickly in this dynamic environment.

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

AspectJunior Nvidia EngineeringJunior Data Scientist
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related fields; knowledge of CUDA, GPU architectureBachelor's or Master's in Data Science, Statistics, or related fields; programming in Python, R, SQL
Work EnvironmentHardware-focused, engineering labs, GPU development teamsData analysis teams, research environments, software development
Industry UsageTechnology, hardware manufacturing, AI hardware accelerationTech, finance, healthcare, research institutions
Common Search/ComparisonYesYes

Junior Nvidia Engineers focus on GPU hardware, CUDA programming, and hardware development, often working in engineering labs. In contrast, Junior Data Scientists analyze data, develop models, and work with statistical tools. Both roles require strong programming skills but differ in their core focus and industry applications.

What are the most commonly searched types of Nvidia Engineering jobs in Georgia? The most popular types of Nvidia Engineering jobs in Georgia are:
What job categories do people searching Junior Nvidia Engineering jobs in Georgia look for? The top searched job categories for Junior Nvidia Engineering jobs in Georgia are:
What cities in Georgia are hiring for Junior Nvidia Engineering jobs? Cities in Georgia with the most Junior Nvidia Engineering job openings:
Infographic showing various Junior Nvidia Engineering job openings in Georgia as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% In-person job distribution.

Sr Advanced AI Engineer

Honeywell

Atlanta, GA • On-site

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago


Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

67th of 538 rated manufacturers


Job description


As a Senior Advanced AI Engineer, you will design, develop, and deploy AI-driven solutions for smart buildings and industrial automation systems. Your primary focus will be building advanced ML models, integrating them into real-world control environments, and driving innovation across HVAC, lighting, security, and energy optimization. You will collaborate cross-functionally, mentor junior engineers, and influence multiple projects with your technical expertise.
Responsibilities
  • AI Solutions Design & Integration
    • Design and integrate AI/ML models into Building Management Systems (BMS) and Industrial Control Systems (ICS), including SCADA and PLC environments.
    • Implement real-time API-based and batch-inference workflows.
    • Develop model feedback loops to support continuous learning and performance improvement.
    • Build algorithms for real-time decision-making using sensor, IoT, and industrial process data.
  • Data Engineering
    • Partner with Data Engineering teams on ETL workflows and data preparation for large-scale building and industrial datasets (e.g., HVAC telemetry, energy consumption, machine performance).
    • Contribute to feature engineering and ensure data readiness for modeling
    • Support the development of training pipelines that leverage model registries and tracking systems.
  • Innovation & Research
    • Explore emerging technologies such as generative AI, digital twins, multimodal foundation models, and autonomous control systems.
    • Lead proof-of-concept initiatives and mentor junior engineers through early-stage experimentation.
    • Translate innovative concepts into practical solutions for automation and building intelligence.
  • Performance Optimization
    • Collaborate with MLOps teams to optimize real-time inference across platforms (AKS, GKE, on-prem microk8s).
    • Work with production-ready inference runtimes such as vLLM, ONNX Runtime, and NVIDIA Triton.
    • Contribute to model conversion, quantization, and optimization for efficient inference.
    • Partner with platform engineers on deployment strategies, scalability, and monitoring.
  • Compliance & Security
    • Ensure all AI solutions comply with cybersecurity standards and industrial safety protocols.
    • Maintain training and inference repositories to meet corporate and industry security requirements.

Qualifications
MUST HAVE
  • Technical Expertise
    • Strong proficiency in Python and ML libraries such as PyTorch, TensorFlow, JAX, XGBoost, and scikit-learn.
    • Experience with Kubernetes, Databricks, or comparable platforms.
    • Familiarity with CI/CD practices for AI/ML workflows.
    • Working knowledge of PySpark for data exploration and pipeline contributions.
    • Strong debugging, profiling, and performance engineering skills in Python.
  • AI/ML Knowledge
    • Expertise in one or more key domains: NLP, time-series forecasting, computer vision, or reinforcement learning.
    • Ability to build models with noisy or sparsely labeled datasets.
    • Experience using MLflow or similar tools for tracking, reproducibility, and model registry.
    • Knowledge of converting models for production inference (TorchScript, ONNX).
    • Experience with model performance optimization (e.g., quantization, latency tuning).
    • Working knowledge of applying, fine-tuning, and optimizing foundation models for domain-specific tasks across text, vision, or time-series modalities.
    • Ability to make informed accuracy-cost trade-offs during model design.
  • Innovation Skills
    • Ability to identify emerging AI trends and translate them into practical solutions.
    • Experience in rapid prototyping, proof-of-concept development, and technology scouting.
    • Strong problem-solving mindset with a focus on creative and disruptive solutions.
  • Cloud & Edge Computing
    • Knowledge of AI/ML offerings from major cloud providers (Azure, GCP, or AWS).
    • Experience deploying AI/ML solutions on edge devices (e.g., NVIDIA Jetson) is a plus but not mandatory.
  • Education & Experience
    • Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's degree preferred.
    • Bachelor's + 6 years of relevant AI/ML experience
    • Master's + 4 years of relevant AI/ML experience
    • PhD + 2 years of relevant AI/ML experience

WE VALUE
  • Experience optimizing deep learning models for NVIDIA Jetson-based edge systems.
  • Experience contributing to platform-agnostic AI/ML solutions.
  • Proven end-to-end ownership of the ML lifecycle, including training, deployment, and feedback loops.
  • Experience with smart building platforms, SCADA systems, or energy management solutions.
  • Demonstrated success delivering innovative AI solutions within automation domains.

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information visit: Benefits at Honeywell
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: 03/27/2026.
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.
About Us
Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906