Junior Machine Learning Engineer

Jobtailor

North Vancouver

On-site

CAD 90,000 - 140,000

Full time

14 days+

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Job summary

ALS is seeking an AI/ML engineer to support the development and deployment of ML models across business functions. You will work with LLMs, tool-using agents, and orchestration workflows to build scalable AI solutions in a hybrid, cloud-enabled environment.

The role emphasizes collaboration with senior engineers, data scientists, and cross-functional teams while adhering to governance and responsible AI practices. Strong Python and cloud skills are required.

Qualifications

Hands-on experience with cloud ML services and model hosting (GCP/Azure/AWS).
Experience with ML model training, evaluation and deployment concepts.
Familiarity with LLMs, embeddings, and retrieval-augmented generation (RAG).
Experience with APIs, microservices, or integrating ML models into applications.
Proficient in Python and ML libraries (Scikit-learn, Pandas, NumPy).
Exposure to containerization (Docker) and CI/CD workflows.
Experience in cross-functional technical teams and enterprise data environments.

Responsibilities

Support development and deployment of ML/AI models across business units.
Assist in building AI solutions using LLMs.
Contribute to agentic AI systems, including tool-using agents and orchestration workflows.
Develop, train, test, and evaluate ML and DL models.
Work with structured and unstructured data for feature engineering and data prep.
Collaborate with senior AI engineers to improve performance and reliability.
Support cloud-based AI/ML development on Azure, GCP and AWS.
Build model pipelines, experimentation workflows, and deployment processes.
Participate in code reviews, testing, and documentation.
Stay current with trends in ML, generative AI, LLMs and cloud AI services.
Follow security, privacy, governance, and responsible AI practices.

Skills

GCP

ML/DL concepts

Python

APIs & microservices

CI/CD

Docker

Version control

Data environments

Cross-functional teamwork

Cloud platforms

Education

Degree in CS/Data Science/Software Eng/ML/AI

Tools

Scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

Vector Databases

RAG

Job description

Support the development and deployment of machine learning and AI models across ALS business functions
Assist in building AI solutions using Large Language Models (LLMs)
Contribute to Agentic AI systems, including tool-using agents, orchestration workflows, and task automation
Develop, train, test, and evaluate conventional machine learning and deep learning models
Work with structured and unstructured data for model development, feature engineering, and data preparation
Collaborate with senior AI engineers and data scientists to improve model performance, reliability, scalability, and maintainability
Support cloud-based AI and ML development using Azure, Google Cloud Platform (GCP), and AWS
Assist in building model pipelines, experimentation workflows, and deployment processes
Participate in code reviews, technical documentation, testing, and quality assurance activities
Stay current with emerging trends in machine learning, generative AI, LLMs, deep learning, and cloud AI services
Follow ALS standards for security, privacy, data governance, and responsible AI practices

Requirements

Hands-on experience with Google Cloud Platform (GCP)
Experience using cloud AI and machine learning services, model hosting, or MLOps tools
Familiarity with vector databases, embeddings, retrieval-augmented generation (RAG), or semantic search
Experience with APIs, microservices, or integrating machine learning models into applications
Knowledge of version control, testing, CI/CD, and documentation
Exposure to containerization tools such as Docker
Experience working with enterprise data environments or cross-functional technical teams
Degree or diploma in Computer Science, Data Science, Software Engineering, Machine Learning, Artificial Intelligence, or a related technical discipline
Practical experience with machine learning, including model training, evaluation, and deployment concepts
Experience with deep learning frameworks such as PyTorch or TensorFlow
Exposure to Large Language Models (LLMs)
Familiarity with Agentic AI concepts, including autonomous agents, tool calling, workflow orchestration, and AI assistants
Programming experience in Python
Familiarity with scikit-learn, pandas, NumPy, or similar libraries
Experience with at least one major cloud platform, including Azure, Google Cloud Platform (GCP), or AWS
Ability to work effectively in a collaborative, hybrid team environment
Strong analytical thinking and problem-solving skills
Willingness to learn
Ability to sit at a desk and perform general office work for extended periods, with periodic computer/screen use
Must be a citizen or permanent resident of the country applied for, or hold or be able to obtain a valid working visa

Core Competencies

Demonstrates expertise in developing and deploying machine learning and AI models, with a strong focus on Large Language Models (LLMs) and cloud-based AI services. Proficient in collaborating with cross-functional teams to enhance model performance and adhere to security and governance standards.

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