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Lead Machine Learning Engineer
4 years ago
Senior Machine Learning Engineer
Here in EA's Data Science group within Global Analytics and Insights, we're always looking for new members to help expand our horizons, to move our communal thought process. This is a team that's as likely to collaborate with game designers and producers as they are data engineers, so versatility, persistence, entrepreneurship, and passion are keys to becoming a successful contributor. We exist in a world where tasks and measures aren't easily defined by product managers or scrums and where a project’s cadence can have defined deadlines or be as vague as knowing a game's possible launch date years in the future, so our data scientists and machine learning engineers must have strong organizational skills.
Job Summary
We are looking for someone who is above all persistent, adaptable, and eager to learn on the job. You have an engineering mindset always trying to strike a balance among performance, flexibility, and stability in systems. We have a strong team of Data Scientists building models and you can work with them to help handle deployment systems for our models. You will oversee and help establish the architecture and drive the technical implementation for our model deployment system which will need to be flexible, maintainable, adaptable and scalable. You will use the latest cloud technologies such as AWS/GCP to create our model deployment pipeline. We are looking for someone who has a strong track record of creating model deployment pipelines, is a self-starter, and can drive this model deployment product forward with minimal guidance. This will be the first time our team owns our model deployment pipelines, so this is a great opportunity to create a brand-new end-to-end pipeline.
Responsibilities
- Lead the design and implementation of an efficient and scalable machine learning platform with cloud technology.
- Collaborate closely with the central engineer organization and Data Scientists to improve model deployment environment and integrate new features.
- Understand our users’ business needs and data science workflow in order to evaluate model performance and improve the engineering process.
- Apply findings from cutting edge research to help solve challenging product problems.
Qualifications and Skills
- 5+ years software development skills with proficiency in at least Python, C/C++, or Java.
- Experience with successfully applying machine learning to real world problems with deep learning frameworks such as Keras, TensorFlow, PyTorch, etc.
- Knowledge of Python and packages used for data modeling and analysis (e.g. scikit-learn, scipy, numpy, pandas).
- 3+ years of experience in AWS or GCP using tools such as EMR, S3, EC2, Sagemaker.
- Excellent communication skills and strong ability to collaborate with Data Scientists and Engineers.
- Strong knowledge of extracting and processing data with RDBMS/NoSQL
Nice to have
- Experience with one or more container ecosystem (Docker, Kubernetes).
- Knowledge of architecture and system design to support a scalable platform.
- Proficiency in building data pipelines with orchestration tools such as Airflow.
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