Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed Hands-on production depth required in: * Document layout analysis and semantic chunking beyond fixed-size or ...
Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed Hands-on production depth required in: * Document layout analysis and semantic chunking beyond fixed-size or ...
LangChain, Hugging Face, GPT models, vector databases * Working knowledge of ML/DL libraries: Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace Transformers, OpenCV, NLTK and BART * Understanding ...
LangChain, Hugging Face, GPT models, vector databases * Working knowledge of ML/DL libraries: Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace Transformers, OpenCV, NLTK and BART * Understanding ...
AI/ML Engineer - Higher Ed
Detroit, MI · On-site
OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face * Vector DBs: Pinecone, Weaviate, pgvector, Chroma * Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI * Data:
AI/ML Engineer - Higher Ed
Detroit, MI · On-site
OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face * Vector DBs: Pinecone, Weaviate, pgvector, Chroma * Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI * Data:
Working knowledge of AI/ML frameworks (LangChain, Langgraph, Hugging Face, OpenAI APIs) * Experience with vector databases and embeddings * Understanding of prompt engineering and AI optimization ...
Working knowledge of AI/ML frameworks (LangChain, Langgraph, Hugging Face, OpenAI APIs) * Experience with vector databases and embeddings * Understanding of prompt engineering and AI optimization ...
Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed Hands-on production depth required in: * Document layout analysis and semantic chunking beyond fixed-size or ...
Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed Hands-on production depth required in: * Document layout analysis and semantic chunking beyond fixed-size or ...
... like Hugging Face * 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). * Advanced ...
... like Hugging Face * 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). * Advanced ...
Data Scientist
Dearborn, MI · On-site
... like Hugging Face * 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). * Advanced ...
Data Scientist
Dearborn, MI · On-site
... like Hugging Face * 3+ years of hands-on experience developing and deploying solutions on major cloud platforms, including Google Cloud Platform (GCP) or Amazon Web Services (AWS). * Advanced ...
Machine Learning and AI Developer
Dearborn, MI · On-site +1
$192K/yr
... Hugging Face, PyTorch or TensorFlow, and MLflow or Vertex AI Experiments * 3+ years of experience designing and evaluating LLM outputs for production systems, including prompt engineering, retrieval ...
Machine Learning and AI Developer
Dearborn, MI · On-site +1
$192K/yr
... Hugging Face, PyTorch or TensorFlow, and MLflow or Vertex AI Experiments * 3+ years of experience designing and evaluating LLM outputs for production systems, including prompt engineering, retrieval ...
... Hugging Face, PyTorch or TensorFlow, and MLflow or Vertex AI Experiments * 3+ years of experience designing and evaluating LLM outputs for production systems, including prompt engineering, retrieval ...
... Hugging Face, PyTorch or TensorFlow, and MLflow or Vertex AI Experiments * 3+ years of experience designing and evaluating LLM outputs for production systems, including prompt engineering, retrieval ...
Hugging Face information
See Michigan salary details
$7.75 - $8.70
3% of jobs
$8.70 - $9.66
5% of jobs
$9.66 - $10.61
6% of jobs
$11.45 is the 25th percentile. Wages below this are outliers.
$10.61 - $11.56
12% of jobs
$11.56 - $12.51
13% of jobs
The median wage is $13.14 / hr.
$12.51 - $13.47
17% of jobs
$13.47 - $14.42
9% of jobs
$15.30 is the 75th percentile. Wages above this are outliers.
$14.42 - $15.37
11% of jobs
$15.37 - $16.32
5% of jobs
$16.32 - $17.28
9% of jobs
$17.28 - $18.23
9% of jobs
$7
$13
$18
How much do hugging face jobs pay per hour?
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What is the difference between Hugging Face vs Machine Learning Engineer?
| Aspect | Hugging Face | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Typically requires knowledge of NLP, deep learning, and Python; certifications are optional | Requires degrees in CS or related fields; experience with ML frameworks; certifications beneficial |
| Work Environment | Collaborative, research-focused, often in tech companies or startups | Development, deployment, and optimization of ML models in various industries |
| Employer & Industry Usage | Used by AI/ML companies, research labs, and open-source communities | Employed 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.
How much does Hugging Face pay?

Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 25 days ago
Thomson Reuters rating
8.9
Based on 19 frontline employees who took The Breakroom Quiz
17th of 426 rated business services
Job description
Lead Applied Scientist, Document Understanding
About the Role
This role sits within the applied science function. You will own the design, development, and production deployment of document understanding systems that directly power Westlaw, PracticalLaw, and CoCounsel. The problems are real, the scale is large, and the expectation is shipped, reliable, measurable impact.
You will work across semantic chunking, document enrichment, knowledge graph construction, and synthetic data generation for complex legal, tax, and accounting content. Multiple product teams depend on what this function delivers.
About You
You hold a PhD in Computer Science, AI, NLP, or a related field, with 8+ years of post-degree industry experience taking NLP and document understanding systems from development to production at scale. You have hands-on depth across the full applied arc - model development, distillation, evaluation, and deployment. You publish, you mentor, and you measure success by what ships and performs in production.
What You'll Do
Design and deploy semantic chunking models for lengthy, non-uniformly structured legal documents with adjustable granularity across use cases
Build document enrichment systems using legal and customer-defined taxonomies
Develop LLM-based knowledge graph construction pipelines that extract and link citations, entities, and legal concepts across diverse legal content
Lead knowledge distillation efforts to compress large models into latency-constrained, production-ready SLMs
Design evaluation frameworks - component-level and end-to-end - using expert annotation and synthetic data
Own technical decisions on architecture, chunking strategy, classification approach, and knowledge extraction methods
Partner with engineering on delivery, reliability, and scale across multiple product lines
Provide technical input to senior leadership on AI strategy and roadmap
Mentor applied scientists and ML practitioners on the team
Required Qualifications
PhD in Computer Science, AI, NLP, or a related field - required
8+ years of post-degree industry experience shipping document understanding, information extraction, or knowledge graph systems into production - not research-only experience
Publications at ACL, EMNLP, ICLR, NeurIPS, SIGIR, KDD, or equivalent
Production Python and experience with PyTorch, Hugging Face Transformers, and DeepSpeed
Hands-on production depth required in:
Document layout analysis and semantic chunking beyond fixed-size or paragraph-based methods
Hierarchical, multi-label document classification with domain-specific and customer-defined schemas
Entity recognition and linking, relation extraction, citation parsing, and knowledge graph construction from unstructured text
LLM-based information extraction, few-shot and multi-task learning, and post-training
Knowledge distillation, model compression, and SLM deployment under latency constraints
Synthetic data generation and annotation workflow design
End-to-end evaluation framework design for document understanding
Preferred Qualifications
Legal document understanding, legal IE, or legal AI experience
Complex document structures: nested hierarchies, cross-references, non-uniform formatting
Retrieval or QA systems over large document collections
RAG and agentic workflows in enterprise settings
Knowledge graph frameworks for legal or enterprise applications
AzureML or AWS SageMaker
#LI-LP2
New Position: This position is open due to an existing vacancy to support our evolving business needs.What's in it For You?
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow's challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
Making a Real-World Impact:We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here.
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