Machine Learning Developer

Title: Senior Machine Learning Developer

Location: Remote (Canada) | Flexible

No C2C or third-party submissions

About Workerbee

Workerbee connects workers with employers through trusted introductions.

By joining Workerbee you can be matched for project-based, contract, or permanent opportunities with leading organizations.

Over time, Workerbee helps you:

• Keep a living record of what you’ve actually accomplished
• See how your experience carries across roles and paths
• Explore options without pressure to apply
• Move through change with clarity instead of urgency

We are connected to those who hire talent and are in need of Senior Machine Learning Developers.

In this work, you will help employers solve complex problems and bring real value through hands-on expertise using machine learning to help build an AI Assistant.

The Sr. ML Developer has an opportunity to join a team of strong developers and work on a high-visibility and high impact product - you will change the way millions of customers globally interact with our product on a day-to-day basis across 150+ countries. The ideal candidate has strong technical skills and a desire to keep up to date with advances in big data technologies.

Your impact will be evident through your effective participation in the entire lifecycle of our software including design, analysis, prototyping, development, testing and support of our products.

What You'll Do

• Develop and implement overall programming including frontend, middle tier and backend solutions in React, Python and a potential mix of databases including SQL, Delta Tables and others
• Develop and implement machine learning models and algorithms that meet business needs and requirements
• Apply machine learning techniques to large datasets to identify trends, patterns, and insights
• Select, fine-tune, and evaluate large language models (LLMs) using domain-specific data to support intelligent product features
• Work with DevOps and MLOps teams to containerize, deploy, and monitor ML components using tools such as Docker, Kubernetes, and model registries
• Participate in research and development of new machine learning techniques and technologies
• Create and manage vector search infrastructure to support semantic search, document retrieval, and memory for LLMs
• Work collaboratively with other developers, data engineers and data scientists to build data pipelines and data processing workflows
• Mentor junior machine learning engineers and provide technical leadership in the team
• Stay up-to-date with the latest developments in machine learning and AI technologies and their applications

AI-accelerated engineering (a core & critical part of the job)

• Use AI tools (e.g., Copilot, Claude, GitHub Copilot Agents, IDE agents) to increase throughput across design, implementation, testing, refactoring, and debugging - without compromising correctness, maintainability, or security.
• Establish practical organizational patterns for AI-assisted development:
• AI-assisted scaffolding + human review
• AI-generated test suites and regression harnesses
• Fast refactors with automated verification
• Agentic workflows for repetitive engineering tasks (migrations, API clients, docs, runbooks)
• Apply secure and responsible usage with no sensitive data leakage, strong review discipline, and traceable change sets.
• Help define repeatable AI-enabled engineering practices that improve the speed, quality, and effectiveness of the team and broader organization.

What You Bring

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 6 years of overall development experience
• At least 2+ years of experience in machine learning and AI software development
• Strong programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-Learn
• Experience with cloud platforms such as AWS, GCP, or Azure and their machine-learning services
• Strong understanding of machine learning fundamentals, such as supervised and unsupervised learning, deep learning, reinforcement learning, and natural language processing
• Comfortable coding against backend technologies including MSSQL, NoSQL, Delta Tables and related technologies such as GraphQL and Pyspark
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment
• Excellent communication skills and ability to explain complex technical concepts to non-technical stakeholders

Why Join Workerbee

• Earlier visibility into opportunities
• Better-fit introductions
• Access to meaningful work
• Less application noise
• A network that improves over time

Workerbee employees will not respond to direct communication attempts via email, phone, social media, or LinkedIn regarding status within the talent network or customer needs. Any such inquiries will not receive a response.

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