Machine Learning Engineer

About the position

Koddi builds advertising marketplaces where publishers can monetize their inventory and advertisers can achieve their performance marketing objectives while prioritizing the customer experience. We're seeking a highly skilled Machine Learning Engineer to join our Data Science team. Come play a pivotal role in developing and deploying innovative models at scale. This role requires prior experience deploying complex models in high throughput, low-latency situations. Other elements for success in this role are a strong foundation in ML algorithms, a passion for delivering measurable results, and the ability to thrive in a fast paced environment.

Responsibilities

• Work closely with data scientists, software engineers, and business stakeholders to understand company goals and objectives.
• Translate that understanding 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.
• Deploy machine learning models into production environments, collaborating with software engineering teams to ensure scalability, reliability, and maintainability.
• 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.

Requirements

• 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.
• Familiarity with ML development and deployment tools and platforms such as Databricks, MLFlow, Kubeflow Pipelines, Airflow, TensorRT or similar.
• 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.

Nice-to-haves

• Experience implementing complete model lifecycle from inception to deployment to automated retraining for a complex model such as Contextual Bandit, Deep Neural Network, or similar.