Senior Deep Learning Engineer, Owl.co

$150-230k

Python
C++
C
Senior level
New York
Owl.co

Insurance fraud detection platform

Open for applications

Owl.co

Insurance fraud detection platform

21-100 employees

B2BBankingInsuranceFinancial ServicesSaaSCyber Security

Open for applications

$150-230k

Python
C++
C
Senior level
New York

21-100 employees

B2BBankingInsuranceFinancial ServicesSaaSCyber Security

Company mission

To bring the state of the art ML and MLP methods to transform traditionally manual activity into an equitable process.

Role

Who you are

  • Significant experience in the training, fine-tuning, and maintenance of large-scale LLMs, demonstrating a deep understanding of NLP principles and methodologies
  • Proficiency in programming languages such as Python and C/C++, coupled with a strong grasp of systems architecture and optimization techniques
  • Bachelor's degree in Computer Science, Applied Mathematics, or a related field, providing a solid foundation for tackling complex AI challenges
  • Proven track record of deploying ML models in production environments and actively contributing to the machine learning community through publications or participation in relevant forums
  • Familiarity with state-of-the-art deep learning architectures, such as transformers and GPT, and a willingness to stay updated on emerging trends in the field

Desirable

  • Advanced degree (Master's or PhD) in Machine Learning, Computer Science, or a related discipline, showcasing a deeper level of expertise in AI and NLP
  • Prior experience working with distributed systems and data pipelines, enabling seamless integration of AI technologies into large-scale enterprise environments

What the job involves

  • We're currently seeking a Multimodal AI Engineer (NLP) to play a key role in advancing our core intelligence capabilities
  • In this position, you'll collaborate closely with cross-functional teams to design, implement, and optimize systems that are reshaping how insurers detect and handle illegitimate claims
  • Architect and construct robust data pipelines tailored for the training, fine-tuning, and evaluation of Large Language Models (LLMs)
  • Drive optimization efforts to enhance both the speed and accuracy of LLM inference processes, ensuring efficient and reliable performance
  • Take ownership of managing and enhancing the foundational infrastructure supporting Owl.co's LLMs, including model management and orchestration systems

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Insights

Top investors

7% employee growth in 12 months

Company

Company benefits

  • Competitive medical coverage for all team members, including an annual contribution to a Wellness or Health Spending Account
  • Competitive programs to support employees in their RRSP and 401k plan contributions
  • We see face-to-face collaboration as important, but also allow for work-at-home time
  • 4 weeks of paid time off plus additional sick days
  • Allowance towards fitness expenses, favorite activities, or professional development

Funding (last 2 of 5 rounds)

Nov 2021

$21.8m

SERIES B

Oct 2020

$7m

SERIES A

Total funding: $33.4m

Our take

Insurance fraud is an $80B problem annually for American consumers and Owl.co is looking to put a stop to it. The company’s claim monitoring platform is designed to help providers mitigate and prevent fraud, and therefore cut premiums and adjust expenses for insurance customers. The company is currently focused on weeding out ineligible disability and workers' compensation insurance claims.

Owl.co doesn’t use discriminatory data like age, gender, or zip codes in its monitoring procedure, instead connecting to relevant data via a zero-knowledge protocol. This means Owl.co’s solution hits two key trends developing fast in the insurance industry: privacy, and equity. With these set to be two major priorities in the years ahead, Owl.co is smart to position itself at the centre of these two conversations

With clients like the Toronto Stock Exchange, and members of the top 10 North American banks and insurers, Owl.co already commands a strong customer base for its services. If it can secure a reputation for unbiased monitoring, this is likely to only grow.

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Steph

Company Specialist at Welcome to the Jungle