The world leader in Adaptive Behavioural Analytics technology for fraud and risk management is adding a Sr. Machine Learning (ML) Engineer to their Atlanta Data Science team. Using machine learning and anomaly detection, the comany's platform helps financial institutions and organizations around the globe stop fraud in real time.
The company has had tremendous commercial success over the last couple of years and as a result the scale of the systems that we are being asked to deploy have grown massively. The ML Engineering team is a new team being created to help data scientists scale the offline steps required to build high performing real-time fraud detection models.
In addition to strong performance in engineering skills, the role will require an understanding of how supervised Machine Learning systems are trained and deployed, including a working familiarity with classification algorithms.
What you'll do:
- Working with data scientists to develop internal tools for model iteration and data preparation
- Writing systems for making inferences on streaming, real-time data
- Developing and accelerating parallel / distributed / GPU-accelerated machine learning (ML) pipelines
- Optimizing data storage, data processing and computation pipelines
- Implementing and optimizing machine learning classifiers and management of their operational lifecycles
- Experience of designing and developing scalable applications in Java, Python OR a similar language
- Familiarity with modern software development tooling and practices, incuding source control, testing, and code review
- Knowledge of parallel and distributed computing
- Experience with working in a Linux environment
- And most importantly, a small-company attitude: willingness to adapt to a variable role and a great can-do attitude.
- Experience with performance tuning and profiling
- Knowledge of database architectures and data layouts for efficient processing
- Understanding data preprocessing requirements for machine learning algorithms
- Knowledge of or previous experience with training and deploying machine learning systems
- Proven ability to design information-rich tools in a user-friendly way
- Experience with data visualization or graphing libraries
A Human Approach to Staffing
Our Company is committed to the principles of equal employment. We are committed to complying with all federal, state, and local laws providing equal employment opportunities, and all other employment laws and regulations. It is our intent to maintain a work environment which is free of harassment, discrimination, or retaliation because of sex, gender, race, religion, color, national origin, physical or mental disability, genetic information, marital status, age, sexual orientation, gender identity, military service, veteran status, or any other status protected by federal, state, or local laws. The Company is dedicated to the fulfillment of this policy in regard to all aspects of employment, including but not limited to recruiting, hiring, placement, transfer, training, promotion, rates of pay, and other compensation, termination, and all other terms, conditions, and privileges of employment.