Machine Learning/AI Engineer
Role details
Job location
Tech stack
Job description
Architect and refine sophisticated ML models and algorithms, translating complex datasets into actionable solutions.
Engage in the full lifecycle of data modeling projects, from understanding business requirements to deployment and monitoring.
Execute comprehensive data analysis, including preprocessing, feature engineering, and leveraging Generative AI algorithms for novel solutions.
Lead cross-functional collaborations to integrate Generative AI models into our offerings, enhancing product capabilities and user experiences.
Apply advanced analytical techniques to analyze vast datasets, identifying trends, anomalies, and opportunities for improvement.
Execute data preprocessing, feature engineering, and algorithm optimization to enhance model accuracy and efficiency.
Conduct exploratory data analysis to extract valuable insights and influence strategic decisions.
Keep abreast of and implement the latest ML trends, tools, and best practices, including AutoML, MLOps, and interpretability frameworks.
Promote compliance with industry standards and regulatory requirements, emphasizing ethical AI practices.
Requirements
Experience architecting and developing AI or machine learning solutions on platforms such as AWS, Databricks, Azure, Google Cloud and OpenAI.
Software engineering and/or Data Engineering background, especially in one of the major clouds.
Hands-on experience with Deep Learning, LLM, Python, TensorFlow, PyTorch and other AI frameworks
Experience putting ML/AI into production, and ability to talk through best practices and pitfalls.
Benefits & conditions
Competitive salary range: Based on experience and market value