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Principal Machine Learning Engineer | AI Center of Excellence

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Job Description:

Principal Machine Learning Engineer | AI Center of Excellence

This role is available in either of our sweet locations in:

• London
• Stockholm

Do you have a dynamic approach to solving problems and processing data at scale? Are you passionate about building machine learning (ML) tools for data scientists? Do you believe machine learning (ML) can have a material impact on how we do business and want to be a part of the journey to help teams, company- wide, enhance our players’ experiences? Then you could be our new, shiny, Principal ML Engineer!

Your role within our Kingdom

You´ll be part of the AI Center of Excellence (ACE) team at King, working closely together with ML Engineers, ML Research Engineers and Data Scientists. Our mission? Discover potential ML use cases across the company, build data models & pipelines, ML models & infrastructure, provide ML use case services to our games reliably and at scale.

As ML Engineer at King, you will be using the latest technologies to build ML products that democratize ML model training, tuning and deployment across the company. With over 250+ million monthly active users and 50 billion events being uploaded daily, it’s key that you care about writing highly optimized code and care about quality. You’ll be working with both streaming as well as batch data in a highly challenging technical environment.

You will work in collaboration with business stakeholders, both within your team and supporting other teams, on creating value from data. Together with your team members you´ll get to learn on the job every day!

Skills to create thrills

So what about you? You have hands- on experience in various ML projects working as an experienced ML engineer. You are a strong advocate for best practices in ML solutions and you have good intuition on what ML models might be most effective and efficient. You are a technical leader, meaning you will be responsible for developing and evolving the solutions fitting the use cases.

Minimum Requirements:

• MS or PhD in Computer Science/Engineering, Machine Learning, Data Science, Physics, Mathematics, or other engineering/scientific areas with 5+ years of experience.
• Extensive experience working in applied AI/ML and Data Science projects
• Deep knowledge and extensive experience with data science and machine learning concepts and algorithms
• Experience in distributed data processing and modeling (batch & streaming)
• Experience building data pipelines and ML pipelines
• Experience in GCP data products (BigQuery, Cloud Storage, Dataflow, Pub/Sub to name a few)
• Must be a tenacious and self- catalyzing problem solver. Must be able to synthesize disparate data, detect and work around broken data, and investigate every possibility until you are confident you have and understand a thorough solution
• Process- oriented driving toward visibility, accountability, and communication
• Team- oriented, ability to build long- lasting and collaborative relationships effectively. You work selflessly and enthusiastically, serving as a positive catalyst for collaborative solutioning
• You contribute to the expertise in every data and analytic conversation as well as you listen with openness to other’s expertise
• A passion for analytics and diving into as well as experiencing the products on which you work (video game enthusiasm with a solid understanding of the connection of gameplay to spending behavior is a plus)
• Ability to adapt quickly, high tolerance for ambiguity, and ability to coordinate on a team

Tasty bonus skills

Have any sweet experience with one or some of the following areas? Then we sure like to hear about them!

• Development in or exposure to environments/software products in Python and Java
• Experience working with Tensorflow, Pytorch, Flink, Kafka, Spark or similar
• Contributions to open source projects
• We know that you are into games on some level (casual, console, board- games, Uno etc.)

Buzz: Data Modeling, Programmer, ML Engineer, Gaming, GCP, Platforms, AI, ML, TDD, Artificial Intelligence, Machine Learning, Research and development, Data Science

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