Machine Learning Engineer I (Contractor)

We are looking for a Machine Learning Engineer I (Contractor) to join a team building and improving intelligent software solutions. This Long-term Contract position is well suited for someone who enjoys working across model development, data engineering, and production deployment in a hands-on engineering environment. The role offers the opportunity to support both current applications and early-stage concepts by combining technical execution with careful analysis, testing, and documentation.

Responsibilities:
• Build, improve, and verify machine learning algorithms that support product and application objectives.
• Create and maintain end-to-end data workflows that handle ingestion, quality checks, cleansing, and ongoing monitoring.
• Train machine learning models, measure performance against validation criteria, and release models that meet requirements into production environments.
• Contribute to prototype development and exploratory initiatives that help shape future technical solutions.
• Prepare and update technical materials such as evaluation plans, reports, presentations, white papers, test summaries, manuals, and Confluence documentation.
• Execute testing activities, analyze outcomes, and document findings through case studies and structured reporting.
• Partner with engineering and cross-functional teams to translate technical requirements into practical machine learning solutions.

Requirements

• Bachelor’s degree in computer science, computer engineering, mathematics, or a related technical field, or equivalent industry experience.
• 1–3 years of experience in machine learning, deep learning, data mining, statistical analysis, or a closely related area.
• Proficiency in software development with strong programming ability in Python and familiarity with Java or Scala.
• Experience deploying machine learning models and supporting model performance through validation and monitoring practices.
• Knowledge of data pipeline and cloud-related technologies, including tools such as Kafka, Spark, and Docker.
• Ability to create clear technical documentation, reports, and presentations for engineering and project stakeholders.
• Strong analytical thinking and problem-solving skills with the ability to evaluate solutions through testing and reporting.