We are looking for a Machine Learning Engineer who is technically proficient in programming to build machine learning systems and maintain high performing machine learning models in production. Designing machine learning systems requires that you, as the machine learning engineer, is able to frame business problems and design machine learning solutions that can effectively bring value to the company. You will prototype, implement and experiment with machine learning methods to solve business use cases. You will lead efforts to automate, architect and optimise machine learning processes and workflows. You will also help define, execute and enforce best practices for test-driven model development processes for the entire Data Science team in MoneyLion.
Key Responsibilities
Able to frame and contextualize machine learning problems
Research, build and design machine learning systems and models that can solve business problems
Assess, understand and analyse data to select appropriate datasets for data modelling and testing
Identify, prototype and implement appropriate machine learning algorithms and tools to improve our products
Design, execute and monitor machine learning model experiments and metrics
Perform statistical analysis to evaluate and prove business impact of modelling improvements
Automate, architect and orchestrate machine learning processes and pipelines
Monitor, optimise and maintain machine learning solutions in production
Enrich existing machine learning libraries and model development frameworks to empower model development in MoneyLion
Work with MLOps Engineers and Data Scientists to improve systems designs and architectures
Enforce test-driven development and advocate engineering best practices to reduce technical debt in machine learning systems
Develop tools and internal libraries to facilitate model governance over the machine learning development lifecycle
About You
Strong mathematical, statistical or actuarial background
Good programming knowledge and software engineering skills
Must have hands on experience in machine learning, predictive analytics and statistical modelling
Experience developing and deploying machine learning models in production.
Adept at problem solving and troubleshooting using both textbook methods and novel viewpoints
Proficient in Python and SQL
Proficient with machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM
Preferably have experience in building machine learning systems and workflows
Preferably familiar and have experience with MLOps tools such as DVC, MLFlow, Metaflow, Seldon, BentoML
Preferably familiar and have experience with AWS, Docker, Kubernetes.
Solid communication and collaboration skills.
What's Next...
After you submit your application, you can expect the following steps in the recruitment process:
1. Online Technical Test
2. Take-Home Assessment
3. Interview & Discussion of Take-Home Assessment - Hiring Manager (Virtual or face-to-face)
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Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.
