Machine Learning Engineer 5 - AI Foundation - Image domain

What You'll Do

1. Research, design, and implement advanced ML models and pipelines for training and inference at scale, including techniques in computer vision, NLP, deep learning, and generative AI.
2. Integrate Large Language Models (LLMs) and agent-based frameworks to support multimodal creative workflows, enabling rich, context-aware content generation and dynamic user experiences.
3. Collaborate with multi-functional teams to translate product requirements into ML solutions, iterating from proof-of-concept to fully productionized services.
4. Develop robust platforms for continuous model training, experimentation, A/B testing, and monitoring, ensuring that model quality and relevance remain consistently high.
5. Leverage distributed computing technologies and cloud infrastructures to handle large-scale data processing, feature engineering, and real-time inference, optimizing for performance and cost-efficiency.
6. Implement reliable APIs and microservices that serve ML models to end users, ensuring alignment to standard methodologies in security, compliance, scalability, and maintainability.
7. Stay ahead of emerging ML research, tools, and frameworks, evaluating and integrating new technologies such as sophisticated LLMs, reinforcement learning-based agents, and innovative inference optimization techniques.

In the near future, we will expand the model coverage to include more creative tasks. We will also improve the model architectures to achieve better latency and accuracy. Additionally, we will integrate federated learning or domain adaptation strategies to reach diverse audiences.

Basic Qualifications:

1. PhD or Master’s or Bachelor’s in Computer Science or equivalent experience, ML, Applied Mathematics, Data Science, or a related technical field.
2. 14+years of industry experience.
3. Proficiency in Python and Java for ML model development and systems integration.
4. Hands-on experience with deep learning frameworks, including TensorFlow and PyTorch.
5. Demonstrated experience working with LLMs and agent frameworks to develop advanced AI-based experiences.
6. Proficiency in computer vision and NLP techniques for multimodal content understanding and generation.
7. Work experience in Creative Domains, Imaging Domains will be highly useful.
8. Experience in developing and deploying RESTful web services and microservices architectures for applications involving ML.
9. Proficiency with UNIX environments, Git for version control, and Jenkins for CI/CD processes.