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Pytorch Huggingface Jobs in New York (NOW HIRING)

Data Scientist

Manhattan, NY · On-site

$190 - $220/hr

Fluent programming skills in Python, and fluency with modern data science and ML/NLP libraries (PyTorch, Tensorflow, HuggingFace, etc.). * Deep fluency and instincts for data manipulation, treatment ...

HuggingFace's API, OpenAI's API; * Implementing Python code for data analysis, automation, API ... PyTorch, and utilizing cloud environments like Google Cloud Platform (GCP) for deploying and ...

Lead AI Applied ML Engineer

Jersey City, NJ · On-site

$112K - $147K/yr

Experience with one or more ML frameworks - Pytorch, Tensorflow, SciKit, NeMo, Huggingface Transformers * Hands-on experience with AWS services, and Databricks * Experience/Exposure to SQL, NoSQL and ...

New

... keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse * Command of data science and ... HuggingFace, and GPT-x etc.) * Experience with natural language processing toolkits like NLTK ...

... PyTorch, TensorFlow, HuggingFace) - Common application and infrastructure security vulnerabilities and mitigations (OWASP Top 10, CWE 25) - Source code and DevOps management tools (e.g., Github ...

Showing results 41-60

Pytorch Huggingface information

What is a PyTorch Huggingface engineer?

PyTorch Hugging Face developers are professionals who specialize in building and deploying machine learning and natural language processing (NLP) models using PyTorch, an open-source deep learning framework, and the Hugging Face library, which provides a wide range of pre-trained models and tools for NLP tasks. These developers create, fine-tune, and implement models for tasks like text classification, question answering, and language generation. Their expertise includes working with model architectures such as BERT, GPT, and others, as well as integrating models into applications or research projects.

What are the key skills and qualifications needed to thrive as a PyTorch Huggingface engineer?

To thrive as a PyTorch Hugging Face Engineer, you need a strong background in deep learning, Python programming, and experience with machine learning frameworks, supported by a relevant degree such as computer science or engineering. Familiarity with PyTorch, Hugging Face Transformers library, version control systems like Git, and often cloud platforms (e.g., AWS, GCP) is essential, with certifications in machine learning or cloud technologies being advantageous. Strong problem-solving skills, collaboration, and clear communication help you effectively design, implement, and optimize NLP models in cross-functional teams. These skills ensure you can build state-of-the-art AI solutions efficiently, troubleshoot complex challenges, and deliver impactful results in the fast-evolving field of natural language processing.

How do PyTorch Huggingface engineers typically collaborate with data scientists and researchers in a project setting?

PyTorch Huggingface engineers often work closely with data scientists and researchers to implement, fine-tune, and deploy state-of-the-art machine learning models. Collaboration involves regular discussions to understand project objectives, translating research ideas into efficient code, and iterating on model performance. Engineers are responsible for optimizing model pipelines, integrating new features, and ensuring compatibility with the Huggingface ecosystem. Effective communication and teamwork are essential, as projects usually require frequent feedback loops and joint problem-solving sessions.

What is the difference between Pytorch Huggingface vs Machine Learning Engineer?

AspectPytorch HuggingfaceMachine Learning Engineer
CredentialsProficiency in Python, deep learning frameworks, familiarity with NLP librariesDegree in CS, data science, or related field; experience with ML models
Work EnvironmentResearch labs, AI startups, tech companies focusing on NLP and deep learningTech companies, consulting firms, R&D departments across industries
UsageDeveloping NLP models, fine-tuning transformers, deploying AI solutionsDesigning, building, and deploying ML models across various domains

While Pytorch Huggingface specializes in NLP model development using transformer architectures, Machine Learning Engineers work across diverse ML applications. Pytorch Huggingface skills are often part of a Machine Learning Engineer's toolkit, but the roles differ in scope and focus.

What job categories do people searching Pytorch Huggingface jobs in New York look for?

The top searched job categories for Pytorch Huggingface jobs in New York are:

What cities in New York are hiring for Pytorch Huggingface jobs?

Cities in New York with the most Pytorch Huggingface job openings:

Senior Machine Learning Engineer

Child Mind Institute

Manhattan, NY • On-site

$118K - $148K/yr

Full-time

Medical, Retirement

Re-posted 9 days ago


Job description

About Child Mind Institute

We're dedicated to transforming the lives of children and families struggling with mental health and learning disorders by giving them the help they need. We've become the leading independent nonprofit in children's mental health by providing gold-standard evidence-based care, delivering educational resources to millions of families each year, training educators in underserved communities, and developing tomorrow's breakthrough treatments.


Position Details:

As the Senior Machine Learning (ML) Engineer, you will apply expertise in Natural Language Processing (NLP) and Large Language Models (LLMs) to develop and implement innovative ML solutions that have the potential to make a significant impact in the lives of children and adolescents struggling with mental health issues. You will work with researchers, clinicians, and software engineers within DAIR and across departments to design, prototype, deploy and maintain applied ML solutions to enhance our digital mental health tools.

This is an exempt, full-time, hybrid position located in our NYC headquarters office. The in-office requirement and schedule are subject to change based on the needs of the program and the organization. This position requires a minimum of four (4) days per week in the office, on a schedule determined by your supervisor.

You Will:

● Design, implement, and maintain machine learning models with a focus on NLP and LLMs for real-world application in the mental health field.

● Perform analyses on large datasets using high-performance computing infrastructures.

● Collaborate with cross-functional teams to integrate ML solutions into research projects and mental health tools.

● Develop and maintain data pipelines for training, evaluating, and deploying models.

● Leverage expertise to create innovative solutions to complex problems using state-of-the-art ML methods.

● Ensure data quality, security, and compliance with privacy regulations.

● Perform additional job-related duties as assigned.


You Have:

● Master's degree in Neuroscience, Psychology, Engineering, Computer Science or equivalent combination of education and experience.

● 8+ years of experience in data analysis and data science fundamentals (e.g., algorithms, data structures, data visualization, machine learning).

● 8+ years of experience in at least one scientific programming language (e.g., Python/R, Matlab) and related toolboxes or frameworks (e.g., Tidyverse, Scipy, Sklearn, Polars, Pytorch) is required.

● 5+ years of experience working in a Linux environment, using version control systems (e.g., GitHub), and software virtualization platforms (e.g., Docker).

● 3+ years of practical experience developing and designing production-oriented machine learning technologies and systems, including hands-on experience in NLP and modern ML/NLP.toolchains (e.g., pytorch, tensorflow, SpaCy, HuggingFace, NLTK).

● Experience can be concurrent with education.


Our Benefits


Our great compensation package and benefits include medical insurance, 401(k), paid parental leave, dependent care, discounted tickets and entertainment perks programs. For more information about our benefits, please visit our employee benefits website.


Pay Range

The salary range for the position is posted. Factors such as candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations affect the salary offered within this range. In addition, this salary may be subject to a geographic adjustment (according to a specific city and state and depending on the role), if an authorization is granted to work outside of the location listed in this posting.


#LI-on-site, #LI-hybrid


EEO Disclaimer

Child Mind Institute is committed to fostering an inclusive and equitable workplace where all individuals are treated with respect and dignity. We are proud to be an equal opportunity employer and prohibit discrimination and harassment of any kind.


We provide equal employment opportunities to all employees and applicants for employment, regardless of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity, gender expression, age, national origin, ancestry, citizenship status, marital status, military or veteran status, physical or mental disability, genetic information, medical condition, or any other characteristic protected by applicable federal, state, or local laws.


In compliance with California law, we also prohibit discrimination based on reproductive health decision-making, status as a victim of domestic violence, sexual assault, or stalking, or any other category protected by the California Fair Employment and Housing Act (FEHA). In New York, we extend this prohibition to include status as a victim of domestic violence, familial status, or any other characteristic protected by the New York State Human Rights Law (NYSHRL).


Child Mind Institute is dedicated to ensuring accessibility and reasonable accommodations for individuals with disabilities or medical conditions. If you require an accommodation to participate in the application process or perform your job, please contact our HR Department at hr@childmind.org


This policy applies to all aspects of employment, including recruitment, hiring, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, benefits, and training.