Machine Learning Engineer

Applies strong data engineering and machine learning expertise to industrialize predictive and prescriptive solutions across big datasets. He/she handles both streaming and non-streaming analytics use cases and applies deep understanding of analytics and data science to engineer performant and robust code as well as applying best in class development frameworks.

RESPONSIBILITIES:

• Refactor prototypes of predictive models into high performing production-ready solutions.
• Work closely with Data Scientists to create analytical variables, metrics, and models.
• Work closely with data scientists to solve difficult engineering and machine learning problems and produce high-quality code.
• Choose and use the right analytical libraries, programming languages, and frameworks for each task.
• Contribute to building client capabilities by coaching team members on data science methodologies and approaches. Contribute to best coding and engineering practice across AI projects.
• Build/refactor/develop code into reusable libraries, APIs, and tools.

Requirements

• 1-4 years' experience in software engineer with exposure to statistical and/or data science role.
• 5-10 years for Senior ML Engineer.
• SKILLS BSc/MSc in computer science, mathematics or related technical discipline.
• Deep knowledge and proven experience with optimizing machine learning model in a production context.
• Experience with Python or Scala is required.
• Background in programming in C, C++, Java is beneficial.
• Exposure to both streaming and non-streaming analytics.
• Experience with SQL, Spark, Pandas, Numpy, SciPy, Statsmodels, Stan, pymc3, Caret, Scikit-learn, Keras, TensorFlow, Pytorch, Databricks is beneficial.
• Experience working with large data sets, simulation/optimisation and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.