Machine Learning Resident

6 months ago

Edmonton, Canada Alberta Machine Intelligence Institute Full time

Taher Abbasi, Machine Learning Scientist

**About the Role**

**About the Client**

MiddleAI is an Alberta-based startup that is proud to have partnered with both Amii and AWS to commercialize groundbreaking new Generative AI “Action” models. Our research focus has been primarily on ethical, goal-based, multi-agent ecosystems that can reason and take action autonomously on behalf of Large Workforce Companies.

**About the Project**

As our name suggests, we are aiming to be the “middleware” between existing systems; much like humans often are in the “corporate machine”. You will join a team of like-minded, self-motivated nerds focussed on solving a narrow use case related to managing large workforces, scheduling and internal customer support.

Armed with our proprietary dataset, and an armful of Compute Credits, you’ll work with us to build the future of work for middle managers everywhere. We work in Python, and are currently leveraging Bedrock, Pinecone and Caffeine.

**Required Skills / Expertise**

Are you passionate about building great solutions? You’ll be presented with opportunities to both personally and professionally develop as you build your career. We’re looking for a talented and enthusiastic individual with a solid background in machine learning, specifically NLP, LAMs and LLMs.

**Key Responsibilities**:

- Design, implement, and optimize ML algorithms for both predictive modeling and Natural Language Processing (NLP) tasks (summarization, Q&A, etc.)
- Identify, prepare, and optimize large structured and unstructured datasets for ML training
- Conduct applied research on ML techniques, with a focus to understanding and addressing the limitations of existing models
- Collaborate with project team and stakeholders to develop minimum viable products (MVPs) and client focused solutions
- Engage in regular client meetings, contributing to presentations and reports on project progress
- Optimize ML pipelines to ensure efficiency, scalability, and real-time processing capabilities
- Support the productionalization and deployment of models in client environment

**Required Qualifications**:

- Completion of a graduate level program or higher (M.S./Ph.D) in Computer Science, ML or Engineering
- Research or project experience in machine learning, specifically using NLP tools and techniques
- Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, PyTorch, Pandas, Tensorflow, JAX)
- Familiarity with linux, Git version control, and writing clean code
- A positive attitude towards learning and understanding a new applied domain
- Must be legally eligible to work in Canada

**Preferred Qualifications**:
**Non-Technical Requirements**:

- Desire to take ownership of a problem and demonstrated leadership skills
- Interdisciplinary team player enthusiastic about working together to achieve excellence
- Capable of critical and independent thought
- Intellectual curiosity and the desire to learn new things, techniques, and technologies

**Why You Should Apply**

Besides gaining industry experience, additional perks include:

- Work under the mentorship of an Amii Scientist for the duration of the project
- Participate in professional development activities
- Gain access to the Amii community and events
- Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
- Build your professional network
- The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

**About Amii**

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

**How to Apply

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