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DRC is one of the largest educational assessment and curriculum/instruction companies in the industry. Machine Learning Engineer Data Recognition Corporation, Maple Grove MN Company cannot provide sponsorship for this role Please, no agencies or third parties Summary: DRC is seeking a Machine Learning Engineer to advance its Education Data Science initiatives by building and optimizing production‑ready ML models. Working within an interdisciplinary team, you will develop Python‑based AI solutions that run in scalable, cloud‑native environments and support education learning analytics.

The ideal candidate brings 2-5 years of Python experience in an AI or software engineering role, with exposure to modern ML techniques such as LLMs, Transformers, or NLP models. Essential Responsibilities: Design, train, evaluate and iterate on machine learning models to support DRC’s education analytics products Develop high-quality, maintainable Python code for model training, experimentation and evaluation workflows Collaborate closely with MLOps and DevOps engineers to ensure models are reliably deployed and operating in production environments Diagnose and communicate issues related to model performance, data quality, or deployment behavior Work with data scientists, psychometricians, and software engineers to support ML workflows and ensure scalable infrastructure for research and analytics. Contribute to best practices for model versioning, reproducibility and monitoring.

Required Qualifications: 2-5 years of professional experience with Python. Experience with ML frameworks such as TensorFlow or PyTorch Experience preparing datasets, training models and evaluating performance Hands-on experience with NLP techniques and large language models (e.g., transformers) Proficiency with data science tools and programming languages (e.g., Python, R, SQL). Ability to communicate technical findings and issues clearly across teams Familiary with deploying ML models to cloud-based environments (AWS preferred) Understanding of CI/CD concepts and how models move from experimentation to production Ability to identify and articulate deployment related issues without owning implementation Preferred Qualifications (nice to have, not required): Associates or Bachelor’s degree in Computer Science, Information Systems, Data Science or related technical field.

Hands-on experience working with large language models and prompt engineering (e.g., OpenAI) Understanding of the unique challenges and requirements of educational assessment data Experience working with version control (Git) and a collaborative development workflow Essential Job Requirements: Be able to work under supervision and accept feedback Familiarity with Microsoft Office Suite Relate effectively and work respectfully with diverse work groups Ability to consistently perform well during times of increased workload Set and meet deadlines Manage multiple job functions simultaneously Reporting to this position: No direct reports DRC retains the right to change or assign other duties to this position No Agencies, Please Company cannot provide sponsorship for this position www.datarecognitioncorp.com All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. DRC offers a comprehensive benefits program that allows employees to make choices that best meet their current and future needs. We offer many benefits, including medical, wellness, dental, and vision insurance, a 401(k), flexible spending and health savings accounts, short and long-term disability insurance, and life insurance.

DRC also offers a generous paid time off policy and community service leave. Data Recognition Corporation is an Affirmative Action/Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

The salary range is a guideline. Compensation will be based on skills, knowledge, and experience.