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Nvidia Machine Learning Jobs in Atlanta, GA (NOW HIRING)

Sr Advanced AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Experience optimizing deep learning models for NVIDIA Jetson-based edge systems. * Experience ... machine performance). * Contribute to feature engineering and ensure data readiness for modeling

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Nvidia Machine Learning information

See Atlanta, GA salary details

$24.5K

$41K

$84.6K

How much do nvidia machine learning jobs pay per year?

As of Jul 22, 2026, the average yearly pay for nvidia machine learning in Atlanta, GA is $40,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,300.00 and $44,200.00 per year, depending on experience, location, and employer.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

What is a Nvidia Machine Learning job?

A Nvidia Machine Learning job involves developing and optimizing AI models, deep learning frameworks, and GPU-accelerated applications. Engineers in this role work on cutting-edge research, building scalable ML solutions, and improving performance on Nvidia hardware like GPUs and AI accelerators. They collaborate with software and hardware teams to enhance AI capabilities across industries such as gaming, healthcare, and autonomous systems. Strong coding skills in Python, C++, and experience with ML frameworks like TensorFlow or PyTorch are often required.

What are the key skills and qualifications needed to thrive in the Nvidia Machine Learning position, and why are they important?

To thrive in an Nvidia Machine Learning role, a deep understanding of machine learning algorithms, proficiency in programming languages like Python or C++, and a solid background in mathematics or computer science are essential. Experience with Nvidia's CUDA, TensorRT, cuDNN, and familiarity with modern deep learning frameworks such as TensorFlow or PyTorch are highly valued, as are relevant certifications in AI or data science. Strong problem-solving skills, teamwork, and effective communication distinguish top candidates in collaborative, fast-paced environments. These skills are crucial for developing and optimizing AI solutions that leverage Nvidia’s advanced hardware and software platforms.

Does NVIDIA do machine learning?

Nvidia offers extensive tools and platforms for machine learning, including GPUs optimized for training and deploying models. Many machine learning engineers and researchers use Nvidia hardware and software frameworks like CUDA and cuDNN to accelerate AI development. The company also provides AI-focused products and solutions for various industries.

Is it hard to get hired at NVIDIA?

Getting hired for a machine learning role at NVIDIA can be competitive due to the company's focus on advanced technology and innovation. Candidates typically need strong technical skills in deep learning, programming, and relevant experience, along with a solid educational background. The hiring process often involves multiple interviews and technical assessments to evaluate expertise and problem-solving abilities.

What are some common challenges faced by professionals in Nvidia Machine Learning roles?

One common challenge in Nvidia Machine Learning roles is optimizing models to fully leverage GPU architectures for both performance and efficiency, which requires continuous learning as the technology rapidly evolves. Team members often work on complex, large-scale projects that demand close collaboration across software, hardware, and research divisions. Navigating the fast pace of innovation and contributing effectively to cross-functional teams is essential for success. However, these challenges also make the role exciting and offer excellent opportunities for professional growth and hands-on experience with state-of-the-art AI solutions.

Is ML a high paying job?

Machine Learning roles, including positions like Nvidia Machine Learning engineers, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and company, but these jobs tend to offer above-average compensation compared to many other tech roles.
What are the most commonly searched types of Nvidia Machine Learning jobs in Atlanta, GA? The most popular types of Nvidia Machine Learning jobs in Atlanta, GA are:
What job categories do people searching Nvidia Machine Learning jobs in Atlanta, GA look for? The top searched job categories for Nvidia Machine Learning jobs in Atlanta, GA are:
Infographic showing various Nvidia Machine Learning job openings in Atlanta, GA as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $40,951 per year, or $19.7 per hour.
Sr Advanced AI Engineer

Sr Advanced AI Engineer

Honeywell

Atlanta, GA • On-site

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 183 frontline employees who took The Breakroom Quiz

67th of 534 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 crossfunctionally, mentor junior engineers, and influence multiple projects with your technical expertise.

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.

MUST HAVE

  • Technical Expertise
    • Strong proficiency in Python and ML libraries such as PyTorch, TensorFlow, JAX, XGBoost, and scikitlearn.
    • 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, finetuning, and optimizing foundation models for domain-specific tasks across text, vision, or timeseries 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, proofofconcept development, and technology scouting.
    • Strong problemsolving 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 platformagnostic AI/ML solutions.
  • Proven endtoend 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.

  • 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 realtime API-based and batchinference workflows.
    • Develop model feedback loops to support continuous learning and performance improvement.
    • Build algorithms for realtime decisionmaking using sensor, IoT, and industrial process data.
  • Data Engineering
    • Partner with Data Engineering teams on ETL workflows and data preparation for largescale 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 proofofconcept initiatives and mentor junior engineers through earlystage 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, onprem microk8s).
    • Work with productionready 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.

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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