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Entry Level Nvidia Machine Learning Jobs (NOW HIRING)

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Machine Learning Engineer

New York, NY · On-site

You'll work across training infrastructure, inference optimization, and reinforcement learning ... NVIDIA GPU programming (Triton, CUTLASS, custom CUDA kernels) and deep NCCL knowledge * FP8 or FP4 ...

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Senior Machine Learning Engineer

$107K - $146K/yr

Senior Machine Learning Engineer Career Renew is recruiting for one of its clients a Senior Machine ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

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Nvidia

Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership. * Mentor interns and junior researchers to develop technical growth within the team.

Apple

Staff Machine Learning Engineer

Seattle, WA

$171K - $302K/yr

Ray Data, NVIDIA DALI, WebDataset, or Mosaic StreamingDataset Performance engineering for I/O-bound ... machine learning, with hands-on experience across the end-to-end ML workflow - including data ...

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Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

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As of Jun 25, 2026, the average hourly pay for entry level nvidia machine learning in the United States is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $18.99 per hour, depending on experience, location, and employer.
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Infographic showing various Entry Level Nvidia Machine Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $36,327 per year, or $17.5 per hour.

Machine Learning Engineer - Robot Perception

Maven Robotics

San Francisco, CA

Other

Posted 24 days ago

Job description

Company Overview

Maven Robotics is building the world's leading general-purpose AI robots.

We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Machine Learning Engineer - Robot Perception to design, implement, test, and deploy robot perception algorithms that power our robots' ability to understand and interact with the world.

In this role you will:

  • Develop, train, and deploy ML-based perception algorithms for object detection, pose estimation, tracking, and scene understanding.
  • Integrate sensor fusion techniques using cameras, depth sensors, IMUs, and tactile feedback.
  • Optimize real-time perception pipelines for low-latency and robust performance in dynamic environments.
  • Work closely with hardware engineers to design sensor configurations and optimize perception models for onboard deployment.
  • Contribute to our broader AI and autonomy stack, ensuring seamless integration with reasoning, manipulation, planning and control.
  • Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers.
Qualifications

Must-have:

  • MS or PhD in machine learning, computer science, robotics, or a related field.
  • Strong background in computer vision, deep learning, and sensor fusion.
  • Proficiency in Python and C++, with experience in frameworks like PyTorch, TensorFlow, OpenCV, and ROS.
  • Hands-on experience with real-world robotics perception systems (e.g., SLAM, 3D reconstruction, multimodal perception).
  • Experience working with hardware, including setting up and calibrating cameras, LiDAR, and other sensors.
  • Experience with data collection, preprocessing, and management in the context of training ML models.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

  • Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
  • Experience in:
    • Developing models that can handle noisy, incomplete, or sparse data.
    • Deployment of ML models to edge devices for real-time inference (e.g., NVIDIA Jetson).
    • Accelerating ML training processes using GPU, TPU, or other HW accelerators.
    • General knowledge of robotics principles, including kinematics, dynamics, and control.

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