Summary
What you’ll impact
Our company is seeking ML engineers to build the core intelligence behind its AI-powered search, recommendation, and multimodal retrieval systems. The role involves developing, fine-tuning, and deploying models, running experiments, and scaling large-scale data pipelines to improve user experience and business metrics.
Responsibilities
What you'll do
- Build and deploy ML models for search, recommendation, and discovery.
- Improve multimodal retrieval across text, image, video, and structured data.
- Develop and fine-tune LLMs and vision-language models for production use cases.
- Work on relevance problems including query understanding, recall, ranking, embeddings, and RAG.
- Run experiments, analyze results, and drive measurable improvements in KPIs.
- Process large-scale data and build practical, scalable ML systems.
Requirements
What you’ll bring
- 3+ years of experience in machine learning applied to search, recommendation, ads, feed ranking, or relevance.
- Strong fundamentals in ML, deep learning, NLP, or multimodal learning.
- Hands-on experience with retrieval, ranking, embeddings, relevance, optimization, or RAG.
- Experience with multimodal models is strongly preferred.
- Familiarity with LLM fine-tuning methods such as SFT, LoRA, PEFT, RLHF, or DPO is a plus.
- Strong programming skills in Python, Go, or C++.
- Comfortable working in a fast-moving, high-ownership startup environment.