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Hugging Face Jobs in Howell, MI (NOW HIRING)

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See Howell, MI salary details

$8

$14

$19

How much do hugging face jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for hugging face in Howell, MI is $14.46, according to ZipRecruiter salary data. Most workers in this role earn between $12.16 and $17.12 per hour, depending on experience, location, and employer.

Can you make money on Hugging Face?

Hugging Face is a platform that offers opportunities for data scientists, machine learning engineers, and developers to monetize their skills through jobs, freelance projects, or contributing to open-source models. Earning potential depends on the type of work, experience, and whether you are employed directly or working independently. Building a strong portfolio and expertise in NLP and AI tools can increase income opportunities on the platform.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, educators, and skilled tradespeople, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced judgment, and hands-on skills that are difficult for AI to replicate. Continuous learning and adaptability remain important for job security in an evolving technological landscape.

What are Hugging Face jobs?

Hugging Face jobs refer to employment opportunities at the company focused on developing and maintaining open-source machine learning tools, especially in natural language processing. Roles may include software engineering, research, data science, and product management, often requiring skills in Python, deep learning frameworks, and collaboration in a tech environment.

How much do Hugging Face engineers make?

Hugging Face engineers' salaries vary based on experience, role, and location, but generally range from $100,000 to $180,000 annually. Senior positions and specialized roles in machine learning or software engineering tend to offer higher compensation, often including stock options and benefits.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

What cities near Howell, MI are hiring for Hugging Face jobs? Cities near Howell, MI with the most Hugging Face job openings:
Advanced Engineering & Research Intern

Advanced Engineering & Research Intern

Isuzu Motors America LLC

Plymouth, MI

$20 - $34/hr

Other

Posted 20 days ago


Job description

Isuzu Technical Center of America is seeking an Advanced Engineering & Research Intern to join its operations in Plymouth, MI, for Summer/Fall 2026. The selected candidate will be placed with a preferred agency for employment.

JOB SUMMARY

Supports advanced engineering and research for Level 4 autonomous driving by developing, evaluating, and applying multimodal AI models - including vision-language models (VLMs), vision-language-action models (VLAs), large language models (LLMs), and world models - for data triage, autonomous driving system development, simulation, and verification and validation (V&V). Works closely with Isuzu U.S. and Japan teams, well known autonomous driving partners, and research institutes to build AI-assisted workflows for mining on-road data, identifying edge cases, generating and curating scenarios, analyzing perception/prediction/planning behavior, and improving simulation-based safety evaluation. Works at the intersection of vehicle engineering, robotics, machine learning, data engineering, and safety assurance. Performs tasks of increasing complexity throughout the internship.

% of time spenton each activity

             PRINCIPAL DUTIES & RESPONSIBILITIES

30%

1.

Researches, prototypes, and evaluates VLM, VLA, LLM, and world model approaches for automated data triage, semantic scene understanding, edge-case discovery, and autonomous vehicle safety analysis.

20%

2.

Analyzes multimodal on-road and simulation data (camera, LiDAR, radar, GPS/IMU, CAN, and system logs) to identify safety trends, model failure modes, and data-quality gaps.

20%

3.

Supports scenario mining, generation, and simulation V&V workflows to test autonomous driving perception, prediction, planning, and control behavior.

20%

4.

Collaborates with engineers to integrate AI model outputs into autonomous driving development tools, metrics, dashboards, and simulation pipelines.

10%

5.

Prepares and communicates technical findings, experiment results, and recommended next steps to teams across the U.S. and Japan.

6.

Performs miscellaneous job-related duties as assigned.

ORGANIZATIONAL RELATIONSHIPS

  • Reports to: Manager, Autonomous Driving & MBD

EDUCATION, EXPERIENCE & TRAINING

  • Currently enrolled in a Bachelor's, Master's, or Ph.D. program in Engineering, Computer Science, Data Science, Robotics, Artificial Intelligence/Machine Learning, or a related field
  • Academic focus or coursework in autonomous systems, ML/DL/RL, VLMs, VLAs, LLMs, generative AI, world models, computer vision, sensor fusion, vehicle dynamics, simulation, or V&V is preferred
  • Prior internship, research, or project experience with multimodal data, LLM/VLM evaluation, simulation, autonomous driving/robotics, or automotive systems is a plus, but not required
  • Strong academic standing (e.g., minimum 3.0 GPA or equivalent recommended, 3.5+ preferred)

KNOWLEDGE

  • Foundational understanding of data analysis, statistics, ML/DL/RL, model evaluation, and data curation for large-scale multimodal datasets
  • Basic knowledge of autonomous driving architecture, vehicle sensors, data logs, scenario-based testing, simulation V&V, and vehicle safety systems is a plus

SKILLS & ABILITIES

  • Strong analytical, research, and problem-solving skills
  • Proficiency in Python; familiarity with C++, Linux, Git, SQL, or data pipeline tools
  • Familiarity with ML and simulation tools (e.g., PyTorch, Hugging Face, OpenCV, ROS/ROS 2, CARLA, Simulink, or equivalent) is a plus
  • Ability to evaluate and document AI model behavior, limitations, safety implications, and V&V results
  • Effective communication; ability to work independently and collaboratively across U.S. and Japan teams

PHYSICAL STANDARDS

The employee must be able to access, enter, and retrieve data using a computer.  This is primarily a sedentary position in a controlled office environment which requires only occasional reaching, stooping, and lifting of office files, reports or records, typically weighing 5 lbs. or less.  Requires occasional light lifting (5-25 lbs) and on rare occasions, heavy lifting (60 lbs).   Must be able on rare occasions to bend, crawl, climb, crouch, kneel and reach above shoulder level in the performance of job duties. Must be able to work in hot and cold weather extremes.

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