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Jobs in Kelowna, Canada

Large Language Model (LLM) AI Research Engineer

Upfeat Media, Inc.

Winnipeg
Remote
CAD 70,000 - 110,000
30+ days ago
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Field Data Collector Winnipeg

Upfeat Media, Inc.

Winnipeg
Remote
CAD 30,000 - 45,000
30+ days ago

Field Data Collector Ottawa

Upfeat Media, Inc.

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CAD 20,000 - 30,000
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30+ days ago
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CAD 30,000 - 60,000
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Upfeat Media, Inc.

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CAD 35,000 - 50,000
30+ days ago

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CAD 30,000 - 60,000
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Large Language Model (LLM) AI Research Engineer
Upfeat Media, Inc.
Winnipeg
Remote
CAD 70,000 - 110,000
Full time
30+ days ago

Job summary

A leading company in applied AI seeks a Large Language Model AI Research Engineer passionate about NLP and innovative solutions. This role involves developing datasets, engaging with cutting-edge technologies, and contributing to projects that empower financial success. Ideal candidates will have a strong background in Computer Science or Machine Learning and thrive in a collaborative environment.

Qualifications

  • Bachelor’s degree in Computer Science or Machine Learning required.
  • Experience with Langchain and RAG needed.
  • Proficient in Python with ML libraries (TensorFlow, PyTorch).

Responsibilities

  • Lead development and management of datasets for LLM fine-tuning.
  • A/B test open-source LLMs to improve performance.
  • Create applications using LLMs and related technologies.

Skills

Problem Solving
Attention to Detail
Logical Reasoning

Education

Bachelor’s degree in Computer Science
Bachelor’s degree in Machine Learning

Tools

Langchain
TensorFlow
PyTorch
Job description

About Upfeat

Upfeat is an applied AI lab working on helping people with everyday financial needs. We build AI solutions to improve the financial livelihood of people from all walks of life.

We’ve built an open, collaborative remote-first environment and we love to learn and experiment with new ideas and technologies. We’re proud to appear in the Globe and Mail Report on Business of Canada's Top Growing Companies. In addition to, being ranked in the Deloitte Technology Fast 50 program, and recognized on the Deloitte Technology Fast 500.

Role Description

We’re on the lookout for a Large Language Model (LLM) AI Research Engineer who loves getting their hands dirty in the world of NLP. If you’re the kind of person who enjoys diving into complex problems, playing around with massive data sets and turning big ideas into real-world solutions, then you’ll fit right in!

This role is perfect for someone who likes to work both in a team and independently, bringing innovative ideas to life, especially in the area of LLMs. We’re a rapidly growing company with a mission and we want someone who’s as excited as we are to make a big impact. We are also looking for people that are passionate about empowering the financial success of our customers.


Responsibilities

  • Lead the development and management of datasets specifically tailored for fine-tuning LLMs, aimed at maximizing model efficiency and effectiveness.

  • A/B test different open-source LLMs to enhance performance and applicability.

  • Develop cool applications using LLMs and if you’ve worked with Huggingface that’s a plus.

  • Engage in pioneering projects with langchain and related LLM applications, pushing technology boundaries and trying new things.

Qualifications

  • A Bachelor’s degree in Computer Science or Machine Learning.

  • Experience with Langchain and RAG

  • Experience training / fine tuning and deploying open source LLM’s

  • Proficient in Python with extensive experience in ML libraries like TensorFlow and PyTorch.

  • Exceptional problem solving abilities, meticulous attention to detail and a talent for logical reasoning

Notice for Job Applicants

We are living and thriving on diversity at Upfeat! We thank all applicants, however only those selected for an interview will be contacted.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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