Machine Learning Engineer
6 days ago
Job Title: Machine Learning Engineer
Company: Viggle AI
Location: Toronto, ON
About Us:
Viggle AI is a cutting-edge tech startup backed by top-tier investors. At the forefront of the GenAI revolution, we specialize in controllable video generation for content creators, offering advanced technology that empowers creators to realize their visions.
Our rapidly growing app is loved by creators from Hollywood professionals to TikTokers, boasting over 4 million users and hosting the second-largest Discord community worldwide.
With a world-class research and engineering team, we are developing a groundbreaking foundation model poised to transform the future of content creation. Join us and become part of this pioneering team leading the charge in digital content creation
Job Description:
We are seeking an experienced and driven Machine Learning Engineer to join our dynamic team in Toronto. As a Machine Learning Engineer, you will play a pivotal role in developing, deploying, and optimizing our AI models, contributing to the core technology that powers Viggle AI’s video generation platform. You’ll join our foundation model team to create scalable, efficient models that enhance our user experience and set a new standard in AI-driven content creation.
Key Responsibilities:
- Train and deploy video generation models at scale.
- Design and implement data processing pipelines to drive model accuracy and efficiency.
- Finetune and optimize neural networks for real-time performance.
- Research and apply state-of-the-art algorithms.
- Implement and monitor deployment pipelines, ensure model reliability, scalability, and efficiency.
Qualifications:
- 3+ years in machine learning, specifically in deploying and optimizing models in production environments; experience in consumer products is a plus.
- Strong experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Proficient in video processing, computer vision, and generative models.
- Proficient in Python and familiar with efficient model deployment using Docker and Kubernetes.
- Proficient in large-scale data processing.
- Proficient in model optimization, including quantization, distillation, and latency reduction.
- Familiar with cloud platforms (e.g., AWS, GCP) and distributed computing frameworks.
- Strong communication and collaboration skills, with a passion for solving complex challenges and pushing the boundaries.
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