Pour visualiser la description de poste en français, veuillez sélectionner le français, “Select Language” dans le menu déroulant au haut de la page. Senior Machine Learning, Operations Developer.

We are a global team of creators, storytellers, technologists, experience originators, innovators and so much more. We believe amazing games and experiences start with teams as diverse as the players and communities we serve. At Electronic Arts, the only limit is your imagination.And we make games – how cool is that? We entertain millions of people across the globe with the most amazing and immersive interactive software in the industry. But making games is challenging work. That’s why we employ the most creative, passionate people in the industry.

The Data & Analytics (DnA) function brings both quantitative and qualitative insights to the entire company (including all game teams) through Studio Analytics, Data Developing, Data Science and Machine Learning Developing. We develop our Studio’s data technical capabilities to bring data insights right to the studio partners’ fingertips.

EA serves millions of players with multi-genre online experiences via Live Services. Games of the last decade continue to entertain and engage audiences with new titles launching each year. The common need across all game experiences is modern personalization approaches that enhance and increase player experiences, using the latest Machine Learning technologies to retrofit and augment game features, game systems, and game mechanics. We are looking for a Senior Machine Learning Operations (MLOps) who will work amidst unique technologies to deliver in-game Personalization by building global-scale production systems. You will report to the technical director of AI/ML. If you have a passion for creating advanced analytics data products to allow partners to make crucial decisions, you want to make impacts to help player engagement by providing an autonomous platform; then we want to talk to you.

Responsibilities:

1. Collaborate with Machine Learning Developers, Data Science, Data Architecture, Infrastructure, and Governance teams to design and implement machine learning systems.

2. Maintain scalable ML infrastructure across multiple regions.

3. Create ML pipelines for automating and accelerating ML development and deployment tasks.

4. Build end-to-end ML lifecycle management process, including data extraction and processing, model training and versioning, Hyper parameter tuning, evaluation, and deployment.

5. Implement robust software best practices, such as coding standards, code reviews, source control management, build processes, testing, and operations.

6. Monitor and improve the performance of machine learning models in production.

7. Contribute to the development of best practices for our MLOps strategies.

8. Stay updated on developments in MLOps technologies and frameworks.

Qualifications:

1. Bachelor’s degree in Computer Science, Data Science, or related field.

2. Experience as an MLOps Developer or similar role in Machine Learning.

3. Understanding of cloud computing, data management, and machine learning algorithms.

4. Proficiency with programming languages such as Python, R, or Scala.

5. Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).

6. Experience with infrastructure automation technologies like Docker, Kubernetes, Terraform, etc.

7. Must have an working knowledge of CI/CD principles and tools, including GitHub, GitLab, and Jenkins

8. Knowledge of data structures, data modelling, and software architecture.

9. Understanding of data analysis workflows and machine learning model lifecycle.

10. Comfortable working in an Agile environment.

BC COMPENSATION AND BENEFITS

The base salary ranges listed below are for the defined geographic market pay zones in these locations. If you reside outside of these locations, a recruiter will advise on the base salary range and benefits for your specific location.

EA has listed the base salary ranges it in good faith expects to pay applicants for this role in the locations listed, as of the time of this posting. Salary offered will be determined based on numerous relevant business and candidate factors including, for example, education, qualifications, certifications, experience, geographic location, and business or organizational needs.

BASE SALARY RANGES

  • British Columbia (depending on location e.g. Vancouver vs. Victoria):

º $114,050 – $185,250 CAN Annually

Base salary is just one part of the compensation at EA. We also offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and equity.

Tagged as: Analytics, Data Architecture, Data Extraction, Data Science, Design, Governance, Imagination, Infrastructure, Lifecycle Management, Machine Learning, Management, Mechanics, Operations, Parameter Tuning, Personalization, Production Systems

Print Job Listing
We use cookies to improve your experience on our website. By browsing this website, you agree to our use of cookies.

Sign in

Sign Up

Forgot Password

Job Quick Search

Cart

Cart

Share