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 technology company is developing an advanced AI platform that powers next-generation creative workflows across flagship creative products. The platform focuses on agentic AI, large language models, vision-language models, multimodal capabilities, and intelligent tool orchestration to transform how users create and edit digital content.
The organization is seeking a Staff Agentic ML Engineer to provide technical and architectural leadership in developing advanced AI systems for creative applications. The role combines deep machine learning expertise with hands-on engineering and system architecture to build reasoning systems, agent orchestration, multimodal integrations, and production-ready AI capabilities.
The successful candidate will have extensive experience with large language models, model fine-tuning, agentic system development, evaluation frameworks, and multimodal AI. The position also requires strong software engineering fundamentals, technical leadership, and the ability to operate effectively in a fast-moving environment where priorities and challenges may evolve.
The Opportunity
- Lead and contribute to LLM and multimodal LLM post-training and evaluation, including fine-tuning, alignment, and domain adaptation.
- Design and implement scalable agent system architectures.
- Develop practical AI agents using frameworks such as LangChain, LangGraph, MCP, and A2A.
- Apply multimodal AI capabilities to image generation and editing workflows.
- Build and own rigorous evaluation frameworks for LLM and agent performance.
- Develop advanced reasoning and orchestration systems for next-generation creative applications.
Key Responsibilities
- Lead the development of next-generation AI agents that enhance and extend creative product ecosystems.
- Drive the architecture and implementation of robust agentic systems combining reasoning, retrieval, tool use, and multimodal capabilities.
- Own end-to-end LLM fine-tuning pipelines, including data curation, training, RLHF/DPO alignment, and evaluation.
- Design and maintain comprehensive evaluation frameworks to measure agent quality, reliability, and safety.
- Implement state-of-the-art LLM techniques for specialized creative applications.
- Mentor and develop engineers and scientists while establishing strong technical and engineering practices.
- Collaborate across teams to integrate advanced AI capabilities into creative workflows.
- Operate effectively in a fast-moving environment where priorities evolve and problems may be loosely defined.
- Maintain strong technical ownership and independent engineering judgment when using AI-assisted development tools.
Required Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field.
- 8+ years of industry experience in machine learning.
- Demonstrated expertise in LLMs, fine-tuning techniques including SFT, RLHF, DPO, and PEFT/LoRA, and production agentic system development.
- Deep experience building evaluation frameworks for LLM and multi-agent systems, including LLM-as-judge, automated benchmarks, and red-teaming.
- Proficiency in PyTorch and agentic frameworks such as LangChain, LangGraph, MCP, and Agent Development Kit (ADK).
- Experience using AI-assisted development tools such as Claude Code, Codex, and Cursor while maintaining independent engineering judgment and technical ownership.
- Strong foundation in data structures, algorithms, and software engineering principles.
- Excellent problem-solving and communication skills.
- Ability to work effectively in fast-moving and ambiguous environments.
Preferred Qualifications
- Experience with multimodal models, including vision-language models.
- Experience with image generation and image editing using multimodal AI.
- Strong experience designing large-scale AI agent architectures.
- Experience leading technical initiatives involving LLMs and generative AI.
- Demonstrated ability to mentor engineers and scientists and establish technical best practices.
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