AI/NLP/Data Engineer

Reposted 17 Days Ago
Be an Early Applicant
2 Locations
In-Office
Mid level
Fintech • Financial Services • Automation
The Role
The AI/NLP/Data Engineer will develop ML and AI models, enhance NLP systems, and build supporting infrastructure while collaborating with teams on deployment and documentation.
Summary Generated by Built In

About Us 

Agent IQ is a recently funded, rapidly growing mid-stage fintech company.  Agent IQ is making intelligent, frictionless digital engagement easy and profitable. Our  Lynq digital engagement platform improves communication and engagement between financial institutions and their customer. The platform has built in AI/automation functionality to seamlessly improve efficiency, help employees and generate insights about customer needs.  We're excited about our growth and  the opportunities ahead as we continue to change the way FIs service their customers in digital space. To achieve this we're building an amazing team, and here’s where you come in. 

Role Description

As a AI/NLP/Large Data Engineer you will be responsible for building and improving ML and gen AI models, and suggestion/support tools, modeling & experimentation frameworks and building out the  technical core of AgentIQ. You will be given opportunity to drive positive technology improvements and develop state of the art yet practical NLP/AI applications. 

Responsibilities 

  • Build and improve NLP/AI models at heart of AgentIQ product
  • Build and improve infrastructure to support NLP/AI modeling, generation, experimentation and deployment
  • Take ownership of NLP/AI trainer tools and data processing pipelines
  • Brainstorm and prototype algorithmic improvements
  • Develop customer specific and financial institutions focused machine intelligence
  • Contribute to deploying/monitoring/debugging models in production 
  • Take ownership of NLP/AI trainer tools and data processing pipelines
  • Collaborate with platform teams on developing new tools and features needed for NLP/AI development and deployment
  • Create and maintain documentation
  • Provide internal training on applicable topics

 Requirements 

  • Passion for improving AI/NLP models and making them more robust and scalable
  • Ability/desire to work on AI/NLP models requiring little/no training data
  • Thrive in a diverse, dynamic environment that leverages multiple tools and languages 
  • The ability to communicate effectively with thoughtfulness and maturity 
  • Make technology decisions that are best for the business of Agent IQ 
  • Experience building production-quality Gen AI, NLP, speech, or deep learning systems
  • Strong software engineering and interpersonal skills
  • Ability and desire to quickly pick up on new topics and techniques
  • Ability to quickly take an idea from conception and prototyping to deployment in production
  • Masters degree or equivalent in AI/ML/NLP or related field
  • 3+ years in related experience

 

Our environment 

  • AWS/GCP hosted infrastructure
  • Linux 
  • Python
  • Airflow
  • Pytorch
  • Node.js
  • Docker

Perks 

  • Competitive salary + equity
  • Full medical/dental/vision benefits
  • Unlimited PTO policy
  • Work from home
  • Google apps, Dropbox, Drive, Slack, Mac (or PC) everything
  • Agent IQ swag
  • Great teammates

This is a remote (work from home) position

Top Skills

Aws,Gcp,Linux,Python,Airflow,Pytorch,Node.Js,Docker
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The Company
San Francisco, California
31 Employees
Year Founded: 2015

What We Do

Agent IQ’s mission is to make sure digital banking stays personal. For years, financial institutions have shifted their focus toward automation and self-service. This may be better for bottom lines, but it has removed the personal from the financial. Agent IQ gives institutions new ways to help clients optimize finances while staying connected to those who help make transactions happen -- no matter how or where banking happens.

We believe that augmenting the human side of banking is a much better way forward than replacing the human altogether. This augmented intelligence applies a pragmatic application of state-of-the-art AI and machine learning and offers the promise of unprecedented scale while keeping the focus on human-to-human communication

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