ZipRecruiter

Log In

1

Pytorch Huggingface Jobs in Wayne, NJ (NOW HIRING)

Attentive

Senior Machine Learning Engineer

New York, NY · On-site

$244K - $320K/yr

Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas You'll get ...

Smarsh

Lead Data Scientist

New York, NY · On-site +1

... 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 ...

Smarsh

Lead Data Scientist

New York, NY · On-site

... 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 ...

TikTok

Technology Internal Audit Lead

New York, NY · On-site

$108K - $208K/yr

... 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 ...

Capital One

Applied Researcher I

New York, NY · On-site

Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data.

Capital One

Lead AI Engineer

New York, NY · On-site

$112K - $147K/yr

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 ...

Capital One

Applied Researcher II

Manhattan, NY

Leverage a broad stack of technologies -- Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more -- to reveal the insights hidden within huge volumes of numeric and textual data.

previous pagenext page

Showing results 21-40

All JobsPytorch Huggingface JobsPytorch Huggingface Jobs in Wayne, NJ

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 are popular job titles related to Pytorch Huggingface jobs in Wayne, NJ?

For Pytorch Huggingface jobs in Wayne, NJ, the most frequently searched job titles are:

What cities near Wayne, NJ are hiring for Pytorch Huggingface jobs?

Cities near Wayne, NJ with the most Pytorch Huggingface job openings:

Pytorch Huggingface jobs near you
Infographic showing various Pytorch Huggingface job openings in Wayne, NJ as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.

Senior Machine Learning Engineer

Attentive

New York, NY • On-site

$244K - $320K/yr

Full-time

Re-posted 13 days ago

Job description

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We're the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.
Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter's work with us to enable billions of interactions that power tens of billions in revenue for our customers.
With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive's team has been consistently recognized for its performance and culture. We're proud to be included in Deloitte's Fast 500 (four years running!), LinkedIn's Top Startups, Forbes' Cloud 100 (five years running!), Inc.'s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index!
About the Role
Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.
You will operate with a high degree of ownership, partner closely with Product and Engineering, and help raise the technical bar across our ML systems in a fast-paced, high-impact environment.
What You'll Accomplish
  • Design, build, and operate scalable machine learning systems used in real-time targeting, decisioning, personalization systems
  • Own ML projects end-to-end, from data exploration and modeling to deployment, monitoring, and iteration
  • Proactively safeguard model and system quality through testing, monitoring, validation, and alerting
  • Collaborate cross-functionally with product, data, and other engineering partners to translate business problems into ML solutions
  • Continuously improve system reliability, performance, and engineering efficiency
  • Contribute to technical direction and best practices across the ML engineering team
  • Mentor and support other engineers through code reviews, design discussions, and knowledge sharing
  • Thrive in a high-impact, fast-paced, late-stage startup environment

Your Expertise
  • 6+ years of professional experience building production machine-learning software systems
  • Proven experience owning ML systems long enough to see the downstream impact of design decisions
  • Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or xgboost
  • Experience with data processing and analytics tools such as pandas, Spark, SQL, and matplotlib
  • Hands-on experience building automated pipelines for data processing, model training, validation, and deployment
  • Experience collaborating with cross-functional teams to deliver ML-powered features
  • Strong communication skills and a high sense of ownership

What We Use
  • Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
  • Our infrastructure runs primarily in Kubernetes hosted in AWS's EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
  • Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
  • Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
For US based applicants:
  • The US base salary range for this full-time position is $244,000 - 320,000 annually + equity + benefits
  • Our salary ranges are determined by role, level and location

#LI-EF1
By applying for this position, your data will be processed as per Attentive's Privacy Policy.
Attentive Company Values
Default to Action - Move swiftly and with purpose
Be One Unstoppable Team - Rally as each other's champions
Champion the Customer - Our success is defined by our customers' success
Act Like an Owner - Take responsibility for Attentive's success
Learn more about AWAKE, Attentive's collective of employee resource groups.
If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience.
At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.

Apply