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Algorithm Scientist Jobs in Vermont (NOW HIRING)

... and scientists. This team collaborates closely to complete comparative effectiveness analyses ... algorithms * Produce analyses to inform Pharmacy and Therapeutics Committee's formulary decisions

senior .net developer

Underhill, VT · On-site

$56.50 - $72/hr

Computer Science, DataStructures, Algorithms, Memory Management * Strong understanding of OOP and modern design patterns using SOLID development practices * Strong knowledge of SOA in terms of design ...

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Algorithm Scientist information

See Vermont salary details

$50.7K

$112K

$137.9K

How much do algorithm scientist jobs pay per year?

As of Jul 15, 2026, the average yearly pay for algorithm scientist in Vermont is $112,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,800.00 and $137,400.00 per year, depending on experience, location, and employer.

What degree do you need to be an algorithm engineer?

Algorithm scientists typically hold at least a bachelor's degree in computer science, electrical engineering, mathematics, or related fields. Many roles require a master's or Ph.D. for advanced research and development, along with strong programming skills in languages like Python or C++ and knowledge of data structures and algorithms.

Is AI a high paid job?

Algorithm Scientists and other AI-related roles are generally well-paid due to high demand for skills in machine learning, data analysis, and programming. Salaries vary based on experience, location, and industry, but AI jobs often offer competitive compensation compared to other tech roles.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Lead Data Scientist, Machine Learning Director, or Chief Data Officer, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 with experience and advanced skills in areas like deep learning and big data tools. These roles typically require extensive experience, advanced degrees, and expertise in programming, statistical analysis, and data management.

Is 40 too late for data science?

As an Algorithm Scientist, age is not a barrier to entering data science. Many professionals successfully transition into data science roles later in their careers by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Experience, continuous learning, and practical skills are more important than age in this field.

How does an Algorithm Scientist typically collaborate with cross-functional teams during the development process?

Algorithm Scientists frequently work alongside data engineers, software developers, and product managers to design and implement solutions. They are often responsible for communicating complex mathematical concepts in accessible terms to ensure alignment across the team. Regular meetings and code reviews are common, allowing for feedback and rapid iteration. This collaborative environment helps ensure that the algorithms developed are both technically sound and practically viable for real-world applications.

What are Algorithm Scientists?

Algorithm Scientists are professionals who design, analyze, and optimize algorithms to solve complex computational problems. They often work in fields like data science, artificial intelligence, finance, and engineering, developing new methods or improving existing ones for processing data efficiently. Their work involves rigorous mathematics, computer science, and research to ensure algorithms are accurate, scalable, and effective for specific applications. Algorithm Scientists may also collaborate with software engineers to implement their solutions in real-world systems.

What are the key skills and qualifications needed to thrive as an Algorithm Scientist, and why are they important?

To thrive as an Algorithm Scientist, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree such as a Master's or Ph.D. in a related field. Proficiency with programming languages like Python or C++, machine learning libraries (e.g., TensorFlow, PyTorch), and experience with data analysis tools are typically required. Strong problem-solving abilities, analytical thinking, and effective communication skills help distinguish top performers in this role. These skills are vital for developing innovative algorithms that solve complex problems, ensuring practical, scalable solutions in technological environments.
What are popular job titles related to Algorithm Scientist jobs in Vermont? For Algorithm Scientist jobs in Vermont, the most frequently searched job titles are:
Infographic showing various Algorithm Scientist job openings in Vermont as of July 2026, with employment types broken down into 3% Locum Tenens, 70% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution, with an average salary of $112,000 per year, or $53.8 per hour.
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Montpelier, VT • On-site

Other

Posted 23 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.