ML Engineer

Responsibilities

• Design and develop machine learning solutions to address business challenges and improve decision‑making through intelligent automation.
• Analyze business requirements and identify suitable machine learning approaches for predictive analytics, classification, forecasting, and recommendation systems.
• Utilize AI and machine learning platforms, AutoML tools, and intelligent services to build scalable and efficient solutions.
• Collect, evaluate, and prepare datasets to ensure data quality, consistency, and suitability for machine learning applications.
• Collaborate with data scientists, software engineers, and business stakeholders to design and implement AI‑driven solutions.
• Evaluate model performance using key metrics, dashboards, and analytical tools to ensure accuracy, reliability, and effectiveness.
• Monitor deployed machine learning systems and recommend improvements, retraining strategies, and performance optimizations.
• Apply data preprocessing, feature selection, labeling, and augmentation techniques using modern machine learning tools and platforms.
• Support the deployment and integration of machine learning solutions across cloud‑based and enterprise environments.
• Develop intelligent workflows and automation processes that enhance productivity, operational efficiency, and business outcomes.
• Create and maintain comprehensive documentation of machine learning solutions, datasets, workflows, and deployment processes.
• Research and evaluate emerging machine learning technologies, tools, and industry best practices to support innovation initiatives.
• Ensure responsible and ethical use of artificial intelligence by promoting fairness, transparency, privacy, and bias mitigation practices.
• Translate complex machine learning concepts into clear business insights and recommendations for technical and non‑technical stakeholders.
• Collaborate with cross‑functional teams to continuously improve machine learning capabilities and deliver measurable business value.