Engineering Lead – Multimodality, Research

🕒 July 22

🇪🇺 Europe – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

poolside

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2023

🤖 Artificial Intelligence

🏢 Enterprise

Artificial Intelligence • Enterprise

poolside is a frontier AI lab and enterprise platform that builds and deploys foundation models, multi-agent systems, and developer-facing tools focused on automating complex software work. The company specializes in on-prem and VPC deployments, security-first integrations, governance, and connectors to enterprise data sources so organizations can run agents and models inside their own boundaries. Poolside embeds research and engineering with customers to deliver outcome ownership, risk controls, and measurable business impact while advancing toward AGI by starting in high-consequence software environments.

📋 Description

• Own Poolside's multimodality direction and capability adoption • Ship our first image-input capabilities • Chart and drive the path from adapter-based to native multimodality • Collaborate on custom evaluations and datasets for multimodal SWE capabilities • Run experiments end to end: hypothesis, implementation, training at scale, analysis • Partner with evals, architecture, data, and post-training teams to land multimodality in Poolside models

🎯 Requirements

• Experience in end-to-end training of production-grade VLMs • Strong LLM training fundamentals: transformers and distributed training at scale • Strong Python programming skills • Pragmatic and high-ownership: you reach for the simplest thing that works and thrive in greenfield ambiguity • *Nice to have:* • - Leadership and 0-1 experience, especially with substantial breadth, ownership, and hands-on contributions • - Distinguished research background on VLMs or multimodal models • - Understanding of the challenges of native multimodality • - Experience building agentic computer use systems

🏖️ Benefits

• Fully remote work & flexible hours • 37 days/year of vacation & holidays • Health insurance allowance for you & dependents • 16 weeks of flexible, full-pay parental leave • Well-being, always-be-learning & home office allowances • Company-provided equipment • Frequent team get togethers • Diverse & inclusive people-first culture