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Pytorch Huggingface Jobs in Raleigh, NC (NOW HIRING)

Principal Data Scientist

Cary, NC · On-site

$50 - $85/hr

Proficiency with PyTorch, HuggingFace, LangChain/LlamaIndex, RAG, Kubernetes, and vector databases. Experience designing production‑grade ML systems with monitoring, evaluation, and observability.

Pytorch Huggingface information

What are the key skills and qualifications needed to thrive as a PyTorch Hugging Face Engineer, and why are they important?

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.

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 Pytorch Huggingface developers?

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.

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.
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Principal Data Scientist

Principal Data Scientist

TEKsystems

Cary, NC • On-site

$50 - $85/hr

Contractor

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

- Education: Master's or PhD Preferred

- 6–12+ years in Data Science / ML Engineering, with deep experience in LLM‑based systems.

Proven experience building multi-agent architectures (planner‑executor, tool‑use agents, ReAct‑style reasoning).

Strong background in RAG, embeddings, retrieval optimization, and evaluation.

Expertise in NLP, transformers, deep learning, and model fine‑tuning.

Proficiency with PyTorch, HuggingFace, LangChain/LlamaIndex, RAG, Kubernetes, and vector databases.

Experience designing production‑grade ML systems with monitoring, evaluation, and observability.

Description

This role leads the design and development of an advanced multi‑agent AI platform that powers intelligent research, drafting, and reasoning capabilities for large‑scale enterprise knowledge environments. You will architect agent frameworks, optimize retrieval‑augmented generation pipelines, fine‑tune language models, and build the infrastructure that enables AI systems to collaborate, plan, and execute complex tasks reliably. The work directly shapes the next generation of AI‑driven professional tools used by experts in high‑stakes domains.

Core Responsibilities

Architect and implement multi‑agent systems capable of planning, tool use, and coordinated task execution.

Design and optimize RAG pipelines including embeddings, hybrid retrieval, reranking, and context‑window strategies.

Fine‑tune and evaluate small, medium, and large language models for domain‑specific reasoning and summarization.

Develop prompt engineering frameworks, guardrails, and automated evaluation suites for agent reliability.

Build scalable ML services and APIs for production deployment in distributed environments.

Collaborate with product, engineering, and domain experts to translate complex workflows into agentic AI solutions.

Establish best practices for model evaluation, observability, safety, and compliance.

Mentor DS/ML engineers and contribute to long‑term AI strategy and architecture.

Required Expertise

6–12+ years in Data Science / ML Engineering, with deep experience in LLM‑based systems.

Proven experience building agentic architectures (planner‑executor, tool‑use agents, ReAct‑style reasoning).

Strong background in RAG, embeddings, retrieval optimization, and evaluation.

Expertise in NLP, transformers, deep learning, and model fine‑tuning.

Proficiency with PyTorch, HuggingFace, LangChain/LlamaIndex, Ray, Kubernetes, and vector databases.

Experience designing production‑grade ML systems with monitoring, evaluation, and observability.

Strong communication skills and ability to lead technical direction.

Preferred Qualifications

Experience in enterprise search, knowledge management, or high‑compliance domains.

Experience with model distillation, LoRA/QLoRA, PEFT, and model compression.

Experience building evaluation frameworks for hallucination, grounding, and agent reliability.

Familiarity with knowledge graphs, symbolic reasoning, or hybrid neuro‑symbolic systems.

Publications, patents, or open‑source contributions in LLMs or agent systems.

Strong coding skills in Python 7+ years

Be a natural problem solver, able to take a lead in collaborating to resolve issues

Proficiency in IDE debugging : VSCODE and PYCHARM

Have communication skills

5+ years of experience in AI and machine learning

Deep understanding of machine learning algorithms, classification models, diagnostic testing of models

Experience working directly and Transformer based architectures including BERT, RoBERTa, T5 etc. Nd familiarity with large language models and fine tuning

Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigation

Working understanding of the business risks associated with applying LLM (LangChain) in a business

Experience working with AWS, RAG, SageMaker, SQL

Skills

data science, nlp, indexing, semantic search, conversational search, langchain, Generative AI, Large language model, Sql, aws, algorithm, artificial intelligence, Retrieval augmented generation, fine-tuning, Python, Machine learning, cloud computing

Top Skills Details

data science,nlp,indexing,semantic search,conversational search,langchain,Generative AI,Large language model,Sql,aws,algorithm,artificial intelligence,Retrieval augmented generation,fine-tuning

Additional Skills & Qualifications

N/A

Experience Level

Expert Level

Job Type & Location

This is a Contract to Hire position based out of Cary, NC.

Pay and Benefits

The pay range for this position is $50.00 - $85.00/hr.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
• Medical, dental & vision
• Critical Illness, Accident, and Hospital
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Voluntary Life & AD&D for the employee and dependents)
• Short and long-term disability
• Health Spending Account (HSA)
• Transportation benefits
• Employee Assistance Program
• Time Off/Leave (PTO, Vacation or Sick Leave)

Workplace Type

This is a fully remote position.

Application Deadline

This position is anticipated to close on Jun 29, 2026.

About TEKsystems

We're partners in transformation. We help clients activate ideas and solutions to take advantage of a new world of opportunity. We are a team of 80,000 strong, working with over 6,000 clients, including 80% of the Fortune 500, across North America, Europe and Asia. As an industry leader in Full-Stack Technology Services, Talent Services, and real-world application, we work with progressive leaders to drive change. That's the power of true partnership. TEKsystems is an Allegis Group company.

The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

About TEKsystems and TEKsystems Global Services

We’re a leading provider of business and technology services. We accelerate business transformation for our customers. Our expertise in strategy, design, execution and operations unlocks business value through a range of solutions. We’re a team of 80,000 strong, working with over 6,000 customers, including 80% of the Fortune 500 across North America, Europe and Asia, who partner with us for our scale, full-stack capabilities and speed. We’re strategic thinkers, hands-on collaborators, helping customers capitalize on change and master the momentum of technology. We’re building tomorrow by delivering business outcomes and making positive impacts in our global communities. TEKsystems and TEKsystems Global Services are Allegis Group companies. Learn more at TEKsystems.com.

The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.

Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.