[Remote] Machine Learning Engineer - Python / ML
Note: The job is a remote job and is open to candidates in USA. Data Recognition Corporation is seeking a Machine Learning Engineer to advance its Education Data Science initiatives by building and optimizing production‑ready ML models. The role involves developing Python‑based AI solutions that support education learning analytics within an interdisciplinary team.
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
Skills
- 2+ years of professional experience with Python
- Experience with ML frameworks such as TensorFlow or PyTorch
- Understanding data science tools and programming languages (such as Python, R, SQL)
- Experience preparing datasets, training models and evaluating performance
- Ability to communicate technical findings and issues clearly across teams
- Ability to identify and articulate deployment related issues without owning implementation
- 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
- Associates or Bachelor's degree in Computer Science, Information Systems, Data Science or related technical field
- 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)
- Understanding of CI/CD concepts and how models move from experimentation to production
- Familiarity with deploying ML models to cloud-based environments (AWS preferred)
- 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
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