AI Research Engineer (Multi-Modal & Vision)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Join a small, high-caliber AI model team to research and deploy vision-language models. You will design training pipelines, build multimodal datasets, optimize for resource-constrained environments, and evaluate model performance, publishing findings where applicable. This role blends research with production-ready engineering across the full model lifecycle in a remote, global team.

Location: Zurich

Workplace: Remote

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
•Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
•Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
•Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
•Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.

Key Requirements

•Degree in Computer Science, Machine Learning, or a related field; MS/PhD preferred.
•Strong experience with multimodal post-training workflows including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.
•Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.
•Demonstrated ability to build and improve vision-language models with measurable results on standard benchmarks or real-world tasks.
•Proven open-source contributions in multimodal AI on GitHub or HuggingFace.

Experience:MultimodalVision-languageAIResearchProduction

Education:Master's

Skills:CommunicationProblem-solvingCollaboration

Languages:English

Tech Stack:MultimodalVision-languagePost-trainingFine-tuningKnowledge distillationReinforcement learningDistributed trainingGPUCompressionEvaluation frameworks

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website

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Tether.io

1 month ago

AI Research Engineer (Multi-Modal & Vision)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Zurich

Workplace: Remote

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
•Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
•Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
•Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
•Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.

Key Requirements

•Degree in Computer Science, Machine Learning, or a related field; MS/PhD preferred.
•Strong experience with multimodal post-training workflows including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.
•Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.
•Demonstrated ability to build and improve vision-language models with measurable results on standard benchmarks or real-world tasks.
•Proven open-source contributions in multimodal AI on GitHub or HuggingFace.

Experience:MultimodalVision-languageAIResearchProduction

Education:Master's

Skills:CommunicationProblem-solvingCollaboration

Languages:English

Tech Stack:MultimodalVision-languagePost-trainingFine-tuningKnowledge distillationReinforcement learningDistributed trainingGPUCompressionEvaluation frameworks

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website