Senior Machine Learning Engineer

Job Description

• A driven intelligent individual with excellent problem solving and research skills, quick to learn and pick new concepts, and able to work independently and in groups.
• Comfortable with reading and assessing academic literature and scientific concepts, evaluating where a concept is viable for implementation and shipping.
• Capable of developing and testing for new and novel ideas where current models fall short.
• Writing maintainable production-quality code and promoting best practices for code quality.
• Build and operate pipelines for accessing and enriching data for machine learning.
• Working individually and closely with colleagues to provide ideas, advice on ML/AI techniques where and when you see the added value of integrating such techniques within the scope(s) of our business partners.
• Capable of designing computational experiments to verify the feasibility of an idea/model, verify the accuracy and computational cost of existing algorithms, and suggesting possible solutions where an approach falls short in any performance category.
• Able to discuss others' work, research plans and findings with your colleagues and able to take on feedback on your work.
• Working with different teams with different backgrounds to steer in our ideas and suggested solutions or novel models to tackle business needs or add to the business capabilities.
• Working with product managers and owners to translate product and business problems in tractable machine learning and AI solutions.

Job Requirements

• 3+ years of practical experience in machine learning or an MSc or MRes in Machine Learning or a related field and at least a year of practical experience.
• A solid understating of machine learning theory and best practices (NLP, computer vision, ..etc).
• Fluency in statics and linear algebra.
• Expert level knowledge with relevant programming languages (we use Python and we are open to any programming language a candidate is fluent in) and frameworks (PyTorch, TensorFlow for example).
• Fluent in data fundamentals; SQL, Oracle, data extraction and manipulation using procedural languages, statistics, and linear algebra. A solid background in data extraction and manipulation tools.
• Practical experience in prototyping, training and evaluating ML models (a plus if said experience is with financial sets).
• Strong problem solving, quantitative and analytical skills.
• Experience with scientific toolsets such as numpy, scipy, sklearn, …etc