Machine Learning Engineer

Job description

Join our team as a Machine Learning Engineer, where you will play a pivotal role in leveraging data-driven solutions to drive innovation and business impact. Reporting to the Director of Data Science, you will collaborate with cross-functional teams to develop and deploy machine learning models that solve complex problems and drive actionable insights. This role requires a strong foundation in machine learning algorithms, hands-on experience in model development and deployment, and a passion for delivering measurable results through data-driven approaches.

What You Will Do

  • Work closely with data scientists, software engineers, and business stakeholders to understand requirements and translate them into machine learning solutions that address business challenges and opportunities.
  • Design, develop, and implement machine learning models and algorithms to solve complex problems across various domains, including but not limited to recommendation systems, natural language processing, and predictive analytics.
  • Collect, preprocess, and analyze data to extract meaningful insights and features that drive model development and optimization.
  • Evaluate and benchmark machine learning models using appropriate metrics and techniques, iterating on designs to improve performance and robustness.
  • Deploy machine learning models into production environments, collaborating with software engineering teams to ensure scalability, reliability, and maintainability.
  • Experience with developing machine learning models at scale from inception to business impact
  • Monitor model performance and behavior in production, proactively identifying and addressing issues to maintain optimal performance and accuracy.
  • Stay current with advances in machine learning research and technologies, exploring new approaches and methodologies to enhance model capabilities and effectiveness.
  • Document methodologies, processes, and findings, sharing insights and best practices with the broader team to foster knowledge sharing and collaboration.
  • Collaborate with stakeholders to understand business goals and objectives, communicating findings and recommendations to drive strategic decision-making and business impact.

Who You Are

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; Master's or Ph.D. degree preferred.
  • Minimum of 3 years of experience in machine learning engineering or related roles, with a strong track record of developing and deploying machine learning models in production environments.
  • Knowledge developing and debugging in Python, GoLang, Perl, and some knowledge in Tensorflow and model deployment tools like Airflow, Databricks, AWS, Docker.
  • Experience with data preprocessing, feature engineering, and model evaluation techniques.
  • Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and experience deploying machine learning models using containerization technologies (e.g., Docker, Kubernetes).
  • Strong understanding of software engineering principles, including version control, testing, and deployment pipelines.
  • Excellent problem-solving skills and attention to detail, with the ability to analyze complex datasets and derive actionable insights.
  • Effective communication and collaboration skills, with the ability to work across teams and communicate technical concepts to non-technical stakeholders.
  • Experience in Agile/Scrum methodologies and working in interdisciplinary teams is a plus.

About Koddi

Koddi is a global technology company with software and services that help top digital marketplaces effectively monetize their first-party audiences through industry-leading commerce media technology and strategy. Our enterprise platforms leverage first-party data to drive marketplace revenue and profit by improving user experience and target shoppers throughout the purchase path. Koddi’s platforms enable any advertiser, any marketplace, in any industry to increase awareness, generate demand, and drive revenue.

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