Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global visual discovery platform is building advanced artificial intelligence and machine learning technologies to help millions of people discover ideas, explore possibilities, and create meaningful experiences. Its AI initiatives span computer vision, multimodal large language models, representation learning, generative modeling, graph neural networks, and recommender systems.
The organization is seeking a Machine Learning Engineer II, Computer Vision Applied Science to contribute to the development of advanced vision-centric large language models and generative AI systems. This role will focus on building models capable of understanding detailed visual information and user aesthetics while enabling communication through visual assets, multimodal search, and text-to-image technologies.
The successful candidate will work with large-scale visual-text datasets to develop production-ready generative models. The role will be part of a collaborative visual modeling team responsible for creating specialized evaluation benchmarks, advancing computer vision research, and contributing to the broader machine learning research community.
Key Responsibilities
- Prototype and develop new model architectures for vision-centric large language models.
- Fine-tune open-source large language models to improve visual perception and tool-use capabilities.
- Develop specialized evaluation benchmarks for vision-centric capabilities, including applications such as fashion style recommendations.
- Read and analyze research papers while participating in technical discussions and brainstorming sessions.
- Contribute to the development of the organization’s broader visual generative AI strategy.
- Collect and curate relevant visual training data for large-scale AI applications.
- Support reinforcement learning from human feedback (RLHF), targeted fine-tuning, and related model optimization initiatives.
- Conduct research and experimentation using large-scale visual-text datasets.
- Publish and communicate research through conferences, academic papers, technical blogs, and other appropriate channels.
- Mentor junior researchers and research interns within the applied machine learning organization.
- Collaborate with engineers, researchers, and product teams to translate research concepts into production-ready machine learning solutions.
Required Qualifications
- 2+ years of industry experience in computer vision.
- Experience working with generative computer vision models.
- Experience working with visual encoders, large language models, or multimodal machine learning systems.
- Hands-on experience with model fine-tuning and machine learning experimentation.
- Master’s degree or PhD in Machine Learning, Computer Science, or a related technical field.
- Strong understanding of machine learning and computer vision concepts.
- Ability to communicate technical approaches clearly and collaborate effectively with research and engineering teams.
Preferred Qualifications
- Publications at leading machine learning conferences.
- Experience developing or researching vision-language models.
- Experience working with multimodal large language models.
- Experience with generative AI and large-scale model development.
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL and data exploration, and engineering workflow acceleration.
- Experience with reinforcement learning from human feedback (RLHF) or related model optimization techniques.
- Experience mentoring junior researchers, engineers, or research interns.
- Strong interest in contributing to the broader machine learning research community.
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