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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.

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 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.

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.

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Pytorch Huggingface jobs near you

Senior Data Scientist - Predictive Analytics

Great American Insurance Group

Cincinnati, OH • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Great American Insurance Group rating

8.8

Company rating: 8.8 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

53rd of 259 rated insurance

Job description

Be Here. Be Great. Working for a leader in the insurance industry means opportunity for you. Great American Insurance Group's member companies are subsidiaries of American Financial Group. We combine a "small company" culture where your ideas will be heard with "big company" expertise to help you succeed. With over 30 specialty and property and casualty operations, there are always opportunities here to learn and grow.
At Great American, we value and recognize the benefits derived when people with different backgrounds and experiences work together to achieve business results. Our goal is to create a workplace where all employees feel included, empowered, and enabled to perform at their best.
Join our Predictive Analytics team within the Business Data & Analytics department! opportunity to work within a highly collaborative team of data professionals focused on solving critical business challenges in the insurance industry. The roles emphasize intellectual growth, innovation, and the practical application of cutting-edge AI technologies to drive business value.
Great American Insurance Group is committed to fostering professional growth through exposure to emerging technologies, cross-functional collaboration, and opportunities to contribute to strategic AI initiatives that shape the future of the insurance industry.
This position is located in our Cincinnati office and will work on a hybrid schedule. Great American's culture is built on connection, shared learning, and strong relationships. To support this, employees in this role are expected to be on-site four days a week, with the flexibility to work one day remotely. Core in-office days are Tuesday-Thursday, with the fourth day determined by business needs.
Essential Job Functions and Responsibilities
  • Leads the analysis of large, complex datasets to identify advanced trends, patterns, and strategic opportunities
  • Architects and leads the design, development, and deployment of sophisticated predictive models for underwriting, pricing, claims, and customer retention
  • Serves as technical lead for advanced LLM implementations, including custom transformer architectures, advanced fine-tuning strategies, and novel generative AI applications
  • Designs and implements complex RAG and Agentic systems with multi-modal capabilities and advanced reasoning
  • Designs and develops evaluation pipelines to assess the quality and effectiveness of Generative AI outputs
  • Leads Vision Language Model initiatives and advanced computer vision projects using OpenCV and cutting-edge Vision AI technologies
  • Mentors junior data scientists and provides technical guidance on complex modeling projects
  • Drives innovation by exploring new data sources, advanced modeling techniques, and emerging AI technologies
  • Collaborates with senior leadership and cross-functional teams to translate complex business challenges into scalable AI solutions
  • Designs and implements enterprise-level data pipelines and automated reporting tools
  • Establishes model governance frameworks and ensures compliance with regulatory requirements
  • Communicates complex technical concepts and strategic recommendations to C-level executives through compelling presentations
  • Monitors and optimizes model performance across the enterprise and ensures data quality at scale
  • May have responsibility for performance coaching of staff and participatory role in talent selection and development
  • Drives AI strategy and roadmap development for the Predictive Analysis team
  • Performs other duties as assigned

Job Requirements
  • Education: Bachelor's degree in Computer Science, Computer Engineering, Data Science, Statistics, or related quantitative field required. Master's or PhD in related field strongly preferred.

  • Experience: 5-6 years of progressive experience in data science and machine learning, with at least 2 years leading complex AI/ML projects and mentoring junior team members.

Required Technical Skills:
  • Advanced Generative AI & LLM Leadership: • Expert-level knowledge of Large Language Models and generative AI architectures • Advanced experience with transformer models, attention mechanisms, and custom model development • Proven track record in BERT, GPT, and other foundation model implementations • Advanced fine-tuning techniques including LoRA, QLoRA, and parameter-efficient methods • Expert-level RAG system design and Agentic RAG implementation • Experience with multi-agent systems and AI orchestration frameworks

  • Advanced Vision AI & Computer Vision: • Expert proficiency in OpenCV and advanced computer vision techniques • Leadership experience with Vision Language Models and multi-modal AI systems • Advanced image processing, object detection, and video analysis • Integration of vision, language, and reasoning capabilities

  • Senior Technical Leadership: • Expert Python programming with deep knowledge of AI/ML ecosystems • Advanced experience with PyTorch, TensorFlow, and HuggingFace transformers • Database optimization and advanced SQL techniques • MLOps and model lifecycle management

  • Cloud & Enterprise Data Platforms: • Advanced Microsoft Azure architecture and AI services • Expert-level Snowflake implementation including: - Advanced Snowflake SQL and performance optimization - Snowflake Cortex AI/ML advanced features and custom implementations - Snowflake Intelligence advanced analytics and semantic search optimization - Snowflake data sharing and marketplace integration • Enterprise data pipeline architecture and governance

  • Leadership & Strategic Competencies: • Advanced statistical modeling and mathematical foundations • Enterprise model deployment and production optimization • Advanced data visualization and executive-level presentation skills • Deep understanding of insurance industry regulations and model governance • Proven leadership and mentoring abilities • Strategic thinking and AI roadmap development • Cross-functional collaboration and stakeholder management

Scope of Job/Qualifications:
Leads complex to large-scale AI/ML projects with enterprise impact. Proven expertise in optimizing advanced models and implementing cutting-edge machine learning solutions. Demonstrates deep understanding of the organization's business and technology operations with ability to drive strategic AI initiatives. Shows comprehensive knowledge of industry trends, regulatory requirements, and emerging technologies in insurance and AI.
Business Unit:
Business Data and Analytics
Benefits:
We offer competitive benefits packages for full-time and part-time employees*. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.
Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process. Learn more at http://www.gaig.com/careers.
*Excludes seasonal employees and interns.

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