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Huggingface Jobs in Texas (NOW HIRING)

Leveraging a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Inventing and introducing state-of-the-art ...

Experience integrating LLMs or generative AI models into applications Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers * Must be able and willing to ...

Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and introduce state-of-the-art LLM ...

Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning frameworks (e.g., pytorch, tensorflow, huggingface), LLM frameworks (e.g., LangChain ...

Experience and proficiency with Python, machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning frameworks (e.g., pytorch, tensorflow, huggingface), LLM frameworks (e.g., LangChain ...

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Huggingface information

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

To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.

What does a typical day look like for an engineer working at Hugging Face?

As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.

What is a Huggingface job?

A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.

What are the most commonly searched types of Huggingface jobs in Texas? The most popular types of Huggingface jobs in Texas are:
Infographic showing various Huggingface job openings in Texas as of June 2026, with employment types broken down into 35% Full Time, 23% Part Time, and 42% Contract. Highlights an 80% In-person, and 20% Remote job distribution.
Compliance, Machine Learning Engineer, Dallas, Vice President

Compliance, Machine Learning Engineer, Dallas, Vice President

Goldman Sachs, Inc.

Dallas, TX

Other

Posted 27 days ago


Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

29th of 141 rated banks


Job description

Are you passionate about delivering mission-critical, high quality machine learning models, using cutting-edge technology, in a dynamic environment? 

OUR IMPACT

We are Compliance Engineering, a global team of more than 300 engineers and scientists who work on the most complex, mission-critical problems. 

We:

  • build and operate a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm. 
  • have access to the latest technology and to massive amounts of structured and unstructured data.
  • leverage modern frameworks to build responsive and intuitive UX/UI and Big Data applications.

Within Compliance engineering, we are hiring for a Machine Learning Engineering role within Models Engineering. The firm is making a significant investment improve the precision/ recall of the Compliance models portfolio in 2024. To achieve that we are hiring experienced MLEs who have experience of developing and deploying ML models for big data in a distributed architecture.

HOW YOU WILL FULFILL YOUR POTENTIAL

As a member of our team, you will:

  • Work with large scale structure and unstructured data. Drive end to end Machine Learning projects that have a high degree of scale and complexity
  • Build infra for machine learning which involves feature engineering and scaling models to work at scale
  • Develop, productionize, and maintain ml models
  • Run ML experiments by constantly tuning the features and the modeling approaches, documenting findings and results
  • Collaborate closely with ML researchers, to accelerate the usage of cutting edge models
  • Perform code reviews and ensure code quality

QUALIFICATIONS

A successful candidate will possess the following attributes:

  • A Bachelor's or Master's degree in Computer Science, or a similar field of study.
  • 10+ years of hands-on experience with building scalable machine learning systems 
  • Solid coding skills and strong Computer Science fundamentals (algorithms, data structures, software design)
  • Expertise in Python & PySpark
  • Experience in working with distributed technologies like Scala, Pyspark, Iceberg, HDFS file formats (avro, parquet), AWS/ GCP,  big data feature engineering.
  • Experience in system design and evaluating the pros and cons of database choices, schema definition for data storage.
  • Extensive experience with Machine Learning and Deep Learning toolkits (Tensorflow, PyTorch, Scikit-Learn, HuggingFace)

Experience in some of the following is desired and can set you apart from other candidates : 

  • Prior experience with LLMs and Prompt Engineering
  • Prior experience in architecting/ deploying ML applications on AWS/ GCP
  • Prior experience in code reviews/ architecture design for distributed systems. 
ABOUT GOLDMAN SACHS

 
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 

 
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

 
We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

 

 
The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869