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Nvidia Machine Learning Jobs in Florida (NOW HIRING)

Persona AI

Robotics Simulation Engineer

Pensacola, FL · On-site

... machine learning, locomotion, manipulation, perception, and devops teams. Your Role: * Build, maintain, and extend simulation environments in NVIDIA Isaac Sim and Omniverse for humanoid robot ...

Deloitte

Senior AI Engineer - SFL Scientific

Miami, FL · On-site

$99K - $137K/yr

... machine learning applications. Responsibilities : • Work with clients to design, develop, and ... Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc. • Live within ...

Deloitte

Finance Analytics & AI Senior Consultant

Tampa, FL · On-site

$110K/yr

Experience deploying machine learning or generative and agentic AI solutions into production ... NVIDIA, Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure; one or more of ...

Persona AI

Robotics Data Pipeline Intern

Pensacola, FL · On-site

D. in Computer Science, Data Engineering, Machine Learning, Robotics, or a related field * Solid ... Experience with NVIDIA's robotics stack (Isaac, Cosmos, GR00T) * Exposure to distributed computing ...

Deloitte

Oracle Gen AI Manager

Tampa, FL · On-site

... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ... Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP ...

Deloitte

Oracle Gen AI Manager

Miami, FL

... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ... Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP ...

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Nvidia Machine Learning information

See Florida salary details

$19.1K

$31.8K

$65.8K

How much do nvidia machine learning jobs pay per year?

As of Jul 1, 2026, the average yearly pay for nvidia machine learning in Florida is $31,822.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,300.00 and $34,400.00 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.
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Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in Florida as of June 2026, with employment types broken down into 2% As Needed, 54% Full Time, and 44% Part Time. Highlights an 88% Physical, 6% Hybrid, and 6% Remote job distribution, with an average salary of $31,822 per year, or $15.3 per hour.

Robotics Simulation Engineer

Persona AI

Pensacola, FL • On-site

Full-time

Posted 25 days ago

Job description

We're looking for a Simulation Engineer to own and expand our NVIDIA Isaac Sim and Omniverse simulation infrastructure. You'll build the digital twin environments, sim assets, and CI/CD pipelines that our autonomy team relies on daily. You will help achieve the vision in which every robot behavior we develop is prototyped, tested, and validated in simulation before it runs on hardware.
As a simulation engineer at Persona, you will have an incredible opportunity to shape the simulation infrastructure that underpins our entire autonomy stack. You will report to the Behavior Coordination Lead and work closely with machine learning, locomotion, manipulation, perception, and devops teams.
Your Role:
  • Build, maintain, and extend simulation environments in NVIDIA Isaac Sim and Omniverse for humanoid robot development.
  • Develop and manage OpenUSD sim assets: robot models, tools, workpieces, customer facility environments (shipyards, steel fabrication plants, industrial sites).
  • Create and maintain physics-accurate digital twins of customer facilities (shipyards and industrial manufacturing) for behavior validation and deployment planning.
  • Integrate all autonomy subsystems (locomotion, manipulation, perception, hands, navigation, welding) to run against Isaac Sim.
  • Design and implement behavior-level CI/CD pipelines that automatically validate robot behaviors in simulation.
  • Prototype and mock-test robot behaviors (welding, navigation, manipulation) in simulation before hardware integration.
  • Develop synthetic data generation pipelines for training perception, manipulation, and navigation models.

We're Looking For:
  • BS, MS, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
  • 3+ years of professional experience in robotics simulation, digital twin development, or physics-based simulation environments.
  • Strong hands-on experience with NVIDIA Isaac Sim and/or NVIDIA Omniverse.
  • Working knowledge of OpenUSD (Universal Scene Description): authoring, composition, referencing, flattening, and debugging USD stage hierarchies.
  • Proficiency in Python; comfortable writing simulation tooling, test harnesses, and automation scripts.
  • Experience with at least one physics engine: PhysX, MuJoCo, Bullet, or Drake.
  • Solid understanding of robot kinematics, dynamics, and articulated body simulation.
  • Experience developing or maintaining CI/CD pipelines for simulation or robotics software.
  • Familiarity with containerization (Docker) and DevOps practices for simulation infrastructure.
  • Ability to create and manage 3D simulation assets (meshes, materials, collision geometry, articulation definitions).

Preferred or Bonus Qualifications:
  • Experience with NVIDIA Isaac Lab for reinforcement learning environment setup and training.
  • Familiarity with NVIDIA Cosmos for synthetic data generation and scene variability.
  • Experience with ROS/ROS 2 and Gazebo simulation.
  • Experience with Unreal Engine or other real-time rendering engines for robotics visualization.
  • Background in manipulation simulation: contact modeling, grasp planning, dexterous multi-fingered hand interaction, and force/torque estimation.
  • Experience with motion capture data pipelines and motion retargeting to robot models.
  • Exposure to behavior trees, task planning, or autonomy stack architecture.
  • Knowledge of Omniverse extensions development and Kit SDK.

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