Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Principal AI/ML Engineer (Large Language Model) (TS/SCI) {S} with Security Clearance
Aurora, CO · Remote
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Principal AI/ML Engineer (Large Language Model) (TS/SCI) {S} with Security Clearance
Aurora, CO · Remote
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as ... Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Senior ML Engineer
Denver, CO · On-site +1
$107.60K - $147.70K/yr
Advanced Python and deep learning proficiency (PyTorch, HuggingFace Transformers, spaCy ... Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role.
Quick apply
Senior ML Engineer
Denver, CO · On-site +1
$107.60K - $147.70K/yr
Advanced Python and deep learning proficiency (PyTorch, HuggingFace Transformers, spaCy ... Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role.
Remote Huggingface information
What are the key skills and qualifications needed to thrive as a Remote Hugging Face Engineer, and why are they important?
To thrive as a Remote Hugging Face Engineer, you need a strong background in machine learning, deep learning frameworks, and proficiency in Python, often supported by a degree in computer science or related fields. Experience with Hugging Face Transformers, PyTorch or TensorFlow, and version control systems like Git is typically required. Excellent communication, self-motivation, and collaboration skills are essential for working effectively in a distributed team environment. These skills and qualities are crucial for building robust AI solutions, contributing to open-source projects, and ensuring project success in a remote setting.
What are some common challenges faced by remote Huggingface engineers when collaborating with global teams?
Remote Huggingface engineers often collaborate with colleagues across multiple time zones, which can make scheduling meetings and ensuring real-time communication challenging. To overcome this, teams rely heavily on asynchronous communication tools, thorough documentation, and clear workflows. Another challenge is staying up to date with rapid developments in machine learning models and open-source contributions, requiring proactive engagement with the Huggingface community and internal knowledge-sharing sessions. Despite these hurdles, remote engineers typically benefit from a flexible work environment and access to a vibrant, supportive team.
What are Remote Huggingface jobs?
Remote Huggingface jobs are positions offered by Hugging Face, a company known for its open-source machine learning and natural language processing tools, that allow employees to work from anywhere outside of a traditional office setting. These roles can include engineering, research, product management, and other tech-related positions. Working remotely for Hugging Face gives employees flexibility while contributing to cutting-edge AI projects and collaborating with an international team using digital communication tools. Remote employees are typically expected to have reliable internet connections and be proactive in virtual collaboration. Hugging Face is committed to supporting remote work and fostering an inclusive, global workplace.
Does Hugging Face offer remote work?
Hugging Face offers remote work opportunities for many roles, including those related to machine learning, software engineering, and research. Employees can often work remotely depending on the position and team requirements, with some roles requiring occasional in-office presence or specific time zone considerations.
What is the difference between Remote Huggingface vs Remote Machine Learning Engineer?
| Aspect | Remote Huggingface | Remote Machine Learning Engineer |
|---|---|---|
| Credentials | Experience with NLP, Python, and ML frameworks; familiarity with Huggingface libraries | Degree in Computer Science or related field; experience with ML algorithms, Python, and cloud platforms |
| Work Environment | Collaborative, often project-based, with a focus on NLP and AI models | Developing, testing, and deploying ML models across various domains, including NLP, CV, and more |
| Industry Usage | Primarily in AI/ML companies, research labs, and startups focusing on NLP | Across tech companies, startups, and research institutions working on machine learning solutions |
Remote Huggingface roles focus on NLP and AI model development using Huggingface libraries, requiring specific NLP expertise. Remote Machine Learning Engineers have broader responsibilities across ML domains, with a wider skill set. Both roles are remote-friendly but differ in specialization and scope.
What are popular job titles related to Remote Huggingface jobs in Colorado? For Remote Huggingface jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Huggingface jobs in Colorado look for? The top searched job categories for Remote Huggingface jobs in Colorado are:
What cities in Colorado are hiring for Remote Huggingface jobs? Cities in Colorado with the most Remote Huggingface job openings:
Other
Medical, Retirement, PTO
Posted 28 days ago
Job description
Job Title: Principal AI/ML Engineer (Large Language Model)
Job Category: Science
Time Type: Full time
Minimum Clearance Required to Start: TS/SCI
Employee Type: Regular
Percentage of Travel Required: Up to 10%
Type of Travel: Local
Anticipated Posting End: 7/31/2026
The Opportunity:
The Principal AI/ML Engineer will support the development of AI/ML algorithms in a multitude of disciplines from object detection/classification, natural language processing, reinforcement learning, and large language models.
Responsibilities:
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Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers
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Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as tasking collections, identifying gaps in collection plans, analyzing patterns of life, and more.
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Fine tune foundation models and building adaptors for new applications (llama factory, PEFT)
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Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate)
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Build custom applications with LLM frameworks such as LangChain, DSPy
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Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc)
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Analyze large multi-domain datasets such as images, text and/or graph data, to identify statistically relevant features to build models that provide analysts with actionable data
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Review relevant publications to understand and apply cutting edge concepts to defense and commercial applications
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Interface with both internal and external leadership to communicate technical status
Qualifications:
Required:
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BS in machine learning, computer science, mathematics, or related fields.
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10+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following:
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Fine-tuning foundational models
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Steering Techniques (e.g Sparse auto encoders, representation tuning)
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Building adapters to use foundational models (e.g. PEFT, llama factory)
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Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.)
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Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone)
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Using LLM Frameworks (e.g. LangChain, DSPy)
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Using AI APIs ( e.g AWS Bedrock, OpenAI)
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Using LLM deployment frameworks (eg llama.cpp, vllm, tgi)
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Developing UIs with ReAct
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Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers
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Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)
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Active TS/SCI U.S. Government Security Clearance
Desired:
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MS or PhD in machine learning, computer science, mathematics, or related fields.
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Experience leading an interdisciplinary team of researchers and software developers
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Experience with any of the following Computer Vision domains:
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Large Language Models and experience identifying ways to incorporate them into new areas and applications
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Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
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Object detection algorithms such as YOLO and Faster-RCNN
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Natural Language Processing algorithms such as BERT
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Generative Adversarial Networks and Variational Autoencoders
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Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines
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Applying clustering algorithms and/or deep neural networks to real life problems
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Implementing tracking and pattern-of-life algorithms
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Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
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Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
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Experience with Linux
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Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
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Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
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Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
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Experience with implementing tracking and pattern-of-life algorithms
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Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
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Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
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Experience shaping and writing proposals
What You Can Expect:
A culture of integrity.
At CACI, we place character and innovation at the center of everything we do. As a valued team member, you'll be part of a high-performing group dedicated to our customer's missions and driven by a higher purpose - to ensure the safety of our nation.
An environment of trust.
CACI values the unique contributions that every employee brings to our company and our customers - every day. You'll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.
A focus on continuous growth.
Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground - in your career and in our legacy.
Pay Range :
There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
Since this position can be worked in more than one location, the range shown is the national average for the position.
The proposed salary range for this position is:
$114,600-$252,100
CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.