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Machine Learning Engineer

Machine Learning Engineer

OnLogicSouth Burlington, VT, US
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We are seeking a talented and motivated Machine Learning Engineer that will play a critical role in designing, developing, and deploying machine learning models and AI solutions that address complex problems and enhance our products and services. You will work closely with other members of our data team as well as business  stakeholders to enable cutting-edge AI solutions. You are responsible for deploying machine learning models and AI tools to drive business value. As OnLogic continues to grow quickly, your ownership of the data infrastructure will be integral to current and future decision making for all departments across the globe. This full-time position will be located on site in South Burlington, VT or Cary, NC.

The team you will be joining :

Our IT team touches every aspect of our business and each of our day to day lives here at OnLogic. Made up of software developers, infrastructure and security experts, systems and network engineers and business technology professionals, our IT team is constantly working to improve our internal systems to make our lives easier, while optimizing our website to do the same for our customers. From the technology we use to do our jobs, to the infrastructure that supports the way we build, test and ship our products, our IT team keeps our business running smoothly.

Learn more about Life at OnLogic.

On this team, you will :

  • Develop, deploy, and maintain ML models in production using local and cloud resources.
  • Determine feasibility for new ML projects that provide actual business value.
  • Work with other members of the IT team and also business subject matter experts  to integrate machine learning models into production systems.
  • Monitor and evaluate the performance of machine learning models in production, ensuring reliability and scalability.
  • Guide business process to support ML implementations and automation.
  • Develop and implement custom solutions.
  • Leverage and fine-tune foundational models and classic ML algorithms.
  • Identify model inefficiencies and failure modes.
  • Perform data preprocessing, feature engineering, and exploratory data analysis to extract meaningful insights from large datasets.
  • Stay up-to-date with the latest advancements in AI and machine learning, and apply this knowledge to ongoing projects.
  • Document model development processes, experiment results, and performance metrics to ensure transparency and reproducibility.
  • Contribute to the development of new AI-powered features and products, identifying opportunities for innovation within the company.

Requirements

  • You have a Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a similar technical or business field or equivalent experience.
  • Proven experience in machine learning model development and deployment, with a minimum of five (5) years of relevant work experience.
  • Proficiency in machine learning and statistical methods and libraries including scikit-learn, opencv, huggingface, and pytorch.
  • Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying machine learning models.
  • Experience with isolation techniques (docker, vagrant, venv,, etc) and understanding of container orchestration (e.g. docker-compose, kubernetes, etc).
  • Analytical Skills : Strong problem-solving skills and the ability to analyze complex datasets to derive actionable insights.
  • Ability to work in the U.S. without visa sponsorship.
  • Who we're looking for :

  • A self starter with the ability to work in a fast paced environment, thinking independently and acting proactively
  • Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
  • Ability to work effectively in a collaborative, fast-paced environment and manage multiple projects simultaneously.
  • Who we are :

    OnLogic employees have the opportunity to shape our future and drive impactful change. We design and manufacture specialized computers and hardware solutions for companies all over the world, helping them to make the seemingly impossible possible. Our computers are designed to work where others fail, and it's our vision to be the first choice in industrial computing. To make that vision a reality, we've built a team of ambitious problem solvers, guided by the company's core values of Open, Fair, Innovative, and Independent. We have an open office, open salaries, and strive to be fair and transparent in our decision making. We encourage input and feedback from every member of our team and look to improve ourselves and our business every single day.

    Diversity is an essential element of our core values. Not just respecting, but actively embracing a variety of backgrounds, life experiences, and opinions, helps us foster innovation, enhances our problem-solving capabilities, and promotes learning and engagement among the members of our team. We strongly encourage those with diverse backgrounds to apply.

    We are committed to providing a safe, inclusive, and harassment-free workplace for all employees. We do not tolerate any form of harassment, discrimination, or bias based on race, ethnicity, gender, sexual orientation, religion, disability, age, or any other protected characteristic.

    To learn more about our values, our mission and what it's like to work at OnLogic, visit www.onlogic.com / careers .

    Benefits

    The salary range for this role is $95,000 to $135,000. We determine final compensation based on discussions with applicants and their experience in similar roles.

  • A competitive Salary based upon your experience and the requirements of the role
  • A comprehensive Benefits package
  • 401k Plan with 3% Employer Contribution
  • An Annual Profit Share Bonus
  • Paid Maternity & Paternity Leave, and Short & Long Term Disability
  • Opportunity to Participate in our Employee Stock Purchase Plan
  • A personal development plan created to help you (and us) grow
  • #LI-Onsite #LI-SBG

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