About this Role

Fandom is growing! Are you an experienced Machine Learning engineer who is ready to set directions for the development of our ML/AI platform to the next level? Are you interested not only in training models, but more importantly in deploying these models at scale and ensuring that these models deliver an actual value?

Our data consists of millions of articles and images as well as petabytes of clickstream logs from sites like Fandom, Metacritic, GameSpot etc. Together with other teams (such as Data Engineering and Data Science) we work to find ways to extract meaning from these massive amounts of data and deliver ML-powered products to our users.

You Will...

• Play an important role in setting up directions for the development of our ML platform to support different phases of ML model lifecycle
• Work in the cloud environment to enable scaling of our ML jobs to handle huge amounts of data and large ML models
• Work towards optimization of time and cost of our ML inference jobs
• Support Data Scientists by providing infrastructure for their needs, helping them in structuring their training code into reproducible pipelines and by productionizing their model prototypes at scale
• Help in expanding our GenAI capabilities, including setting up a semantic search platform for Retrieval Augmented Generation on a large scale
• Extend our capabilities around observability and monitoring of ML models and their results
• Implement MLOps best practices
• Be a part of the most amazing ML Engineering Team!

You Have...

• 5+ years of experience in work as a Machine Learning Engineer or a similar role
• Good understanding of the recent advancements in the area of ML/AI and of state of the art models and frameworks
• Skills in setting up and managing a distributed computing infrastructure, including Infrastructure as a Code concepts
• Experience in working on Cloud platforms, preferably AWS
• Proficiency in Python and experience in some ML-related libraries (like pytorch, langchain)
• Knowledge of MLOps and related tooling and concepts
• Fluency in Polish and English, both written and verbal 
• Very good communication skills
• Genuine teamwork spirit

Bonus Points...

• Experience in AWS Sagemaker 
• Experience with kedro or similar solutions
• Experience in search engines (i.e. Elasticsearch/OpenSearch), including semantic search
• Worked with Big Data tools like Spark, Hadoop etc
• Experience in K8S solutions
• Skills how to set up a pipeline (DAG) in Airflow
• Interest in the entertainment industry

Benefits & Perks

• MacBook Pro and all the gear you need for work
• Free access to a multitude of popular online courses and books sponsored by our company
• Training (unlimited Udemy + more)
• Company stock options
• Company swag packages
• Cafeteria Benefit Program (including private medical care, gym membership, shopping/wellness bonus, etc.)
• VTO (Voluntary Time Off) - a day off every quarter for volunteering non-profit
• Frequent team bonding events
• Flexible work hours & time-off
• Employee Interest and Hobby Groups supported by our company
• Open, energetic and fan-focused, international work environment

About Fandom

Fandom is the world’s largest fan platform where fans immerse themselves in imagined worlds across entertainment and gaming. Reaching more than 350 million unique visitors per month and hosting more than 250,000 wikis, Fandom is the #1 source for in-depth information on pop culture, gaming, TV and film, where fans learn about and celebrate their favorite fandoms. Fandom’s Gaming division manages the online video game retailer Fanatical. Fandom Productions, the content arm of Fandom, enhances the fan experience through curated editorial coverage and branded content from trusted and established publishing brands Gamespot, TV Guide and Metacritic, along with its Emmy-nominated Honest Trailers and the weekly video news program The Loop. For more information follow @getfandom or visit: www.fandom.com.

Fandom is an equal opportunity employer. Fandom values diversity, and all employment decisions are made on the basis of job requirements and individual qualifications.

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