Rumble is a high-growth video platform and cloud services provider that is creating an independent infrastructure. Our mission is to restore the internet to its roots by making it free and open once again.
What you will do:
Rumble is seeking an experienced Principal ML Data Engineer who will be responsible for setting requirements for data collection, preprocessing, analyzing large amounts of data, building / deploying models and algorithms capable of learning and predicting future data points.
In this key role you will be responsible for:
- Analyze large amounts of data to discover trends and patterns to develop a KPI driven solution.
- Identify valuable data sources and set requirements, and assist in the implementation.
- Undertake and execute preprocessing of structured and unstructured data.
- Build / deploy predictive models and machine-learning algorithms from the ground up.
- Propose solutions and strategies to business challenges and KPIs.
- Collaborate with engineering and product development teams.
- Training and retraining ML systems and models as needed.
- Assist in the management and running of ML specific servers / infrastructure / VMs.
- Other duties, as assigned.
Required Qualifications:
- 10+ years building and optimizing large-scale data pipelines, enabling machine learning workflows, and driving data infrastructure strategies across complex, high-volume environments
- 5+ years of combined expert level experience using one or more of the following languages Python, Java, or C++
- 3+ years working with, running and performing administrative tasks on linux based operating systems
- 2+ years of experience of building machine learning models for business application and KPIs
- Algorithm and model development and execution experience for large-scale applications
- Extensive knowledge and practical experience in deep neural networks and other recommendation systems, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), large language models and collaborative filtering techniques.
- Experienced in MLOps to design, implement, and manage scalable pipelines for model deployment, monitoring, and continuous improvement in production environments.
- Strong fundamentals in problem solving, algorithm design and complexity analysis.
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
Preferred Qualification:
- Experience contributing, working with, or maintaining open-source projects.
- Experience working with any or all of the following: SQL, ClickHouse, Kafka and Redis
Desired Qualification:
- Significant peer reviewed scientific contributions in premier journals and conferences are a plus.
- Understanding of network concepts
- Working experience with online video, and ad technologies
Why Our Team Loves Working Here:
- We are making a significant financial impact for our video creator community; we’re proud of their success stories
- We enjoy challenging the status quo and going head-to-head against Big Tech
- We aren’t afraid to try new things; we act fast and want to win
- We pay competitive salaries and provide great benefits
EEO Statement:
Rumble is an equal opportunity employer. We promote an equal playing field where everyone has the same opportunities regardless of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability status, or any other applicable characteristics protected by law. Rumble is an active participant in the e-verify program.
Physical demands of the position:
While performing the duties of this job, the employee is regularly required to sit for prolonged periods of time while using a computer and/or keyboard. The employee is required to communicate verbally and hear. The employee may be required to walk, reach with hands and arms, balance, and stoop or kneel. The employee may occasionally be required to lift and/or move up to 15 pounds. Specific vision abilities required by this job include clarity of vision at approximately 20 inches or less (i.e., working with small objects or reading small print), including the use of computers.
Top Skills
What We Do
The next generation of video and cloud ☁️
NASDAQ Listed | $RUM
