Offer summary

Qualifications:

Experience with Python and libraries, Proficient in AWS services, Familiar with Infrastructure as Code tools, Expertise in machine learning frameworks, Knowledge of agentic frameworks and RAG workflows.

Key responsabilities:

Design and manage AWS cloud infrastructure

Develop and integrate machine learning models

Implement deep learning for code generation

Create responsive frontend components

Optimize LLM interactions and prompt engineering

Job description

Become a Machine Learning Engineer for a multinational Fortune 500 project in Canada. Drive innovation and uphold high technological standards. Apply today to be a vital member of the dynamic team.

Responsibilities:

Design, implement, and manage AWS-based cloud infrastructure, ensuring scalability, security, and reliability.
Utilize AWS services such as EC2, S3, Lambda, RDS, and DynamoDB for cloud operations.
Implement Infrastructure as Code (IaC) using CloudFormation or Terraform to automate and streamline cloud resource management
Develop and integrate machine learning models, including those built on PyTorch and HuggingFace frameworks.
Fine-tune and deploy Large Language Models (LLMs) like GPT-3, GPT-4, or similar transformer-based models for AI-powered applications.
Implement deep learning models for AI code generation, leveraging PyTorch for custom model development and experimentation.
Create dynamic and responsive frontend components using JavaScript frameworks such as React or Vue.js.
Design UIs that enable users to interact with AI-driven code generation features effectively.
Apply NLP techniques to interpret and process input sources such as LUCID diagrams, API specifications, and FIGMA designs.
Use NLP tools for text preprocessing, entity recognition, and other language modeling tasks to support accurate AI code generation
Develop AI models with autonomous behavior by using agentic frameworks, enabling the system to generate code automatically.
Integrate Retrieval-Augmented Generation (RAG) workflows to ensure models retrieve and utilize relevant information dynamically during code generation.
Design prompt engineering strategies to optimize LLM interactions, improving the accuracy and relevance of generated code outputs.
Work on enhancing engineering productivity by developing an AI-powered platform for code generation.

Minimum Qualifications

Experienced with Python and its libraries, including NumPy, Pandas, and sci-kit-learn, for data manipulation, analysis, and machine learning workflows.|
Experience in Natural Language Processing (NLP) to interpret and extract insights from various input sources such as LUCID diagrams, API specifications, and FIGMA designs.
Competent in using AWS services such as EC2, S3, Lambda, RDS, and DynamoDB.
Familiarity with Infrastructure as Code (IaC) tools like AWS CloudFormation or Terraform is essential for managing cloud environments efficiently
Expertise in Machine Learning Frameworks Such as PyTorch and Hugging Faces
Experience with Agentic Frameworks and RAG Workflows
Extensive experience in designing and deploying applications powered by LLMs like GPT-3, GPT-4, or other transformer-based model

APPLY NOW!

NearSource Technologies values diversity and is committed to equal opportunity. All qualified applicants will be considered regardless of their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as protected veterans