Clariti logo
Clariti

Empowering governments to serve efficiently.

Senior AI Researcher

AI Research ScientistMachine Learning EngineerFull TimeRemoteSeniorTeam 51-200H1B No SponsorCompany SiteLinkedIn

Location

Canada

Posted

9 days ago

Salary

$120K - $150K / year

Seniority

Senior

Job Description

Senior AI Researcher

Clariti

• Translate machine learning research into practical, domain-specific solutions • Own applied research and experimentation across computer vision, LLMs, and AI workflows • Drive the design and execution of experiments end to end • Help shape technical direction by identifying high-impact opportunities • Make pragmatic trade-off calls across model accuracy, interpretability, latency, and cost • Share experience with research teammates to encourage rigor in a collaborative environment

Job Requirements

  • 7–10 years of hands-on experience in applied AI research
  • Demonstrated experience taking your own projects from research through to production
  • Deep, demonstrated experience training and fine-tuning models from scratch using modern frameworks
  • Strong proficiency in Python and experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworks
  • Hands-on experience with end-to-end ML workflows on cloud platforms such as AWS, Azure, or GCP
  • Strong software engineering skills and fluency with version control (Git)
  • Significant experience implementing and improving core computer vision and image processing algorithms

Benefits

  • competitive compensation packages
  • well deserved time off
  • benefits to keep you and your family healthy

Related Job Pages

More AI Research Scientist Jobs

Tether.to logo

AI Research Engineer – Multi-Modal, Vision

Tether.to

Bringing real world currency to the blockchain.

Full TimeRemoteTeam 11-50Since 2014H1B No Sponsor

• 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. • Build and scale training workflows across distributed GPU infrastructure. • Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks. • Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development. • Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements. • Publish research findings in top-tier AI conferences and journals where applicable.

India
Tether.to logo

AI Research Engineer – Multi-Modal, Vision

Tether.to

Bringing real world currency to the blockchain.

Full TimeRemoteTeam 11-50Since 2014H1B No Sponsor

• 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. • Build and scale training workflows across distributed GPU infrastructure. • Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks. • Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development. • Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements. • Publish research findings in top-tier AI conferences and journals where applicable.

United Arab Emirates
Tether.to logo

AI Research Engineer – Multi-Modal, Vision

Tether.to

Bringing real world currency to the blockchain.

Full TimeRemoteTeam 11-50Since 2014H1B No Sponsor

• 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. • Build and scale training workflows across distributed GPU infrastructure. • Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks. • Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development. • Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements. • Publish research findings in top-tier AI conferences and journals where applicable.

United Kingdom
Tether.to logo

AI Research Engineer – Multi-Modal, Vision

Tether.to

Bringing real world currency to the blockchain.

Full TimeRemoteTeam 11-50Since 2014H1B No Sponsor

• 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. • Build and scale training workflows across distributed GPU infrastructure. • Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks. • Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development. • Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements. • Publish research findings in top-tier AI conferences and journals where applicable.

Switzerland