We have a flexible work environment and allow remote work depending on one's personal choice ... Tensorflow, HuggingFace * Work on POCs and research prototypes * Provide thought leadership in ...
We have a flexible work environment and allow remote work depending on one's personal choice ... Tensorflow, HuggingFace * Work on POCs and research prototypes * Provide thought leadership in ...
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more * Invent and ... Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA ...
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more * Invent and ... Remote (Regardless of Location): $244,700 - $279,200 for Distinguished AI Engineer Cambridge, MA ...
Senior Director, AI Engineering -Agentic AI Platform(Remote Eligible)
New York, NY · On-site +1
$276K/yr
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more * Invent and ... Remote (Regardless of Location): $286,200 - $326,700 for Sr. Director, AI Engineering Cambridge, MA ...
Senior Director, AI Engineering -Agentic AI Platform(Remote Eligible)
New York, NY · On-site +1
$276K/yr
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more * Invent and ... Remote (Regardless of Location): $286,200 - $326,700 for Sr. Director, AI Engineering Cambridge, MA ...
Sr. Distinguished AI Engineer (Remote Eligible)
New York, NY · On-site +1
$114K - $157K/yr
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and ... Remote (Regardless of Location): $286,200 - $326,700 for Sr. Distinguished AI Engineer Cambridge ...
Sr. Distinguished AI Engineer (Remote Eligible)
New York, NY · On-site +1
$114K - $157K/yr
... AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and ... Remote (Regardless of Location): $286,200 - $326,700 for Sr. Distinguished AI Engineer Cambridge ...
Remote Huggingface information
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 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 the key skills and qualifications needed to thrive as a remote Huggingface engineer?
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 is a remote Huggingface job?
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.
What are the most commonly searched types of Huggingface jobs in New York?
The most popular types of Huggingface jobs in New York are:
What are popular job titles related to Remote Huggingface jobs in New York?
For Remote Huggingface jobs in New York, the most frequently searched job titles are:
What job categories do people searching Remote Huggingface jobs in New York look for?
The top searched job categories for Remote Huggingface jobs in New York are:
What cities in New York are hiring for Remote Huggingface jobs?
Cities in New York with the most Remote Huggingface job openings:
Full-time
Re-posted 4 days ago
Job description
In the Predictive Analytics AI group, we build data-driven, highly distributed machine learning systems. Our engineers and researchers are responsible for architecting and developing these ML services end-to-end overcoming unique challenges that involve building systems that have high throughput availability, consistency, and low latency. The Predictive Analytics AI Group is the central group in Moody's Analytics comprising of researchers and engineers working together to build data-driven customer-facing products, as well as the necessary infrastructure to support the ML services following the industry leading practices. The group has worked on and built some award-winning AI products like Compliance Catalyst, Adverse Media Monitoring, Coronapulse, Quiqspread, News Edge 2.0, ESG and has participated in various internal automation initiatives. The group also regularly publish and present their work in top-tier academic and industry conferences. We have a flexible work environment and allow remote work depending on one's personal choice.
Broadly, we are looking for colleagues who are passionate about:
- Natural language processing
- Information retrieval
- Information extraction
- Graph Neural Networks
- Recommender systems
- Knowledge graphs
- Explainable AI
We'll trust you to:
- Collaborate with colleagues on production systems and applications
- Design, experiment, and evaluate algorithms as well as models using PyTorch, scikit-learn, Tensorflow, HuggingFace
- Work on POCs and research prototypes
- Provide thought leadership in machine learning
- Represent Moody's Analytics at scientific and industry conferences
- Lead collaboration with colleagues and academia to publish research findings in leading academic venues such as ACL, EMNLP, NAACL-HLT, AAAI, KDD, CIKM, SIGIR, ECIR
You'll need to have:
- Ph.D. in CS, ML, Math, Statistics, Engineering, Quant, or relevant industry experience.
- Publication record in top-tier academic conferences and journals
- Proficiency in modern programming languages such as Python
- Proficiency in leading research projects
Nice to have:
- Experience with MLOPs technologies and workflows
- Experience in working with engineering teams on taking research prototypes to production