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Process Modeling Engineer Jobs in Vermont (NOW HIRING)

Vultus Inc

Databricks Engineer

Johnson, VT · On-site +1

The candidate will work on data pipelines, ETL/ELT processes, data transformation, and analytics ... Good understanding of data modeling, ETL/ELT, and data warehousing concepts. * Strong analytical ...

Globalfoundries

Quantum PDK Engineer

Essex Junction, VT · On-site

$98K - $176K/yr

This position supports development of Process Design Kits (PDKs), compact models, and design ... The engineer will work on compact modeling, device libraries, test chip development, and EDA ...

Globalfoundries

Quantum PDK Engineer

Essex Junction, VT · On-site

$98K - $176K/yr

This position supports development of Process Design Kits (PDKs), compact models, and design ... The engineer will work on compact modeling, device libraries, test chip development, and EDA ...

Mach7 Technologies

Senior Security Engineer

Burlington, VT · On-site

$114K - $157K/yr

Conduct threat modeling and architecture security reviews for new features, services, and product ... Define processes for responding to upstream supply chain incidents (e.g. compromised packages ...

Pwc

AI Engineer

Montpelier, VT · On-site

$55K - $187K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... model performance - Managing data pipelines to validate efficient data flow and processing ...

Trioptus

DataOps Engineer

Montpelier, VT · On-site

Implement statistical process control (SPC) and anomaly detection to ensure data reliability ... Design and support governed semantic data models * Assist with the development and validation of ...

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Showing results 21-40

All JobsProcess Modeling Engineer JobsProcess Modeling Engineer Jobs in Vermont

Process Modeling Engineer information

What does a process modeling engineer do?

A Process Modeling Engineer is responsible for designing, analyzing, and optimizing processes within industries such as manufacturing, chemical production, or energy. They use mathematical models and simulation software to predict how processes will perform under various conditions. By creating digital models, they help improve efficiency, reduce costs, and ensure safety and quality standards are met. Their work often involves collaborating with other engineers and stakeholders to implement improvements based on data-driven insights.

What are the key skills and qualifications needed to thrive as a process modeling engineer?

To thrive as a Process Modeling Engineer, you need a strong background in chemical or process engineering, analytical problem-solving skills, and typically a relevant engineering degree. Familiarity with process simulation software such as Aspen Plus, HYSYS, or MATLAB, and understanding of industry standards are crucial for effective modeling and analysis. Strong communication, teamwork, and project management skills help you collaborate with cross-functional teams and convey complex technical information. These skills ensure accurate process optimization, efficient project execution, and drive operational improvements in manufacturing or industrial environments.

What are some typical challenges faced by process modeling engineers when collaborating with cross-functional teams?

Process Modeling Engineers often work closely with teams from operations, R&D, and IT to develop and refine models that optimize manufacturing or chemical processes. A common challenge is translating complex technical data into actionable insights that are easily understood by non-engineering stakeholders. Effective communication and adaptability are key, as project requirements can evolve rapidly and may require balancing competing priorities. Building strong relationships and maintaining open channels for feedback help ensure that process models align with both technical standards and business goals.

What is the difference between Process Modeling Engineer vs Process Improvement Specialist?

AspectProcess Modeling EngineerProcess Improvement Specialist
Required CredentialsBachelor's in Engineering, Industrial Engineering, or related field; proficiency in process modeling softwareBachelor's in Engineering, Business, or related field; certifications like Six Sigma often preferred
Work EnvironmentEngineering teams, manufacturing plants, or R&D labsOperational teams, manufacturing facilities, or corporate offices
Employer & Industry UsageManufacturing, aerospace, automotive, and industrial sectorsManufacturing, healthcare, logistics, and service industries

The Process Modeling Engineer focuses on creating detailed process models using specialized software to optimize workflows. In contrast, the Process Improvement Specialist concentrates on analyzing existing processes and implementing improvements, often utilizing methodologies like Six Sigma. Both roles require similar educational backgrounds but differ in their primary focus and tools used.

What cities in Vermont are hiring for Process Modeling Engineer jobs?

Cities in Vermont with the most Process Modeling Engineer job openings:

Process Modeling Engineer jobs near you
Infographic showing various Process Modeling Engineer job openings in Vermont as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 2% Contract, and 1% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Generative AI Automation Engineer - Remote Job

Essex Junction, VT • On-site

EnthuZiastic
E-Learning • 11 - 50 employees
Learn more about EnthuZiasticexternal

Other

Re-posted 24 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply