Head of Machine Learning

Jobtailor; Vancouver; On-site; CAD 120,000 - 180,000; Full time

Job summary

Jobtailor in Vancouver is seeking a senior ML leader to define strategy, oversee ML and data pipelines, and drive production readiness for IoT and enterprise AI initiatives.

You will mentor a high-performing team, set standards for MLOps, collaborate with product and executive teams, and translate complex problems into scalable ML solutions.

Qualifications

• Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Physics, or a related field.

Responsibilities

• Define and execute the machine learning strategy aligned with product and business objectives.

Skills

Technical Leadership

Mentoring

Collaboration

Technical Communication

Project Management with JIRA

Education

Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Physics, or a related field

Tools

AWS

Azure

Claude

JIRA

PyTorch

Scikit-learn

C programming

Python

Job description

• Define and execute the machine learning strategy aligned with product and business objectives.
• Lead the design and evolution of signal processing and machine learning architectures for production systems.
• Establish technical standards, best practices, and development processes for ML systems.
• Evaluate emerging ML technologies and identify opportunities to enhance product capabilities.
• Provide technical leadership on architecture decisions, model selection, and system performance optimization.
• Oversee development, validation, deployment, and lifecycle management of machine learning models.
• Oversee the design, optimization, and scalability of signal processing pipelines.
• Define model performance metrics and drive improvements through evaluation and experimentation.
• Ensure robustness, maintainability, and scalability of production ML infrastructure, data pipelines, and supporting databases.
• Oversee MLOps practices, including model versioning, reproducibility, monitoring, and continuous improvement.
• Establish standards for dataset acquisition, quality, governance, and lifecycle management.
• Lead field data collection initiatives and expand/refine training datasets.
• Innovate data labeling, preprocessing, quality assurance, and representativeness methodologies.
• Collaborate with Product Management, Engineering, and executive leadership on the AI roadmap and development priorities.
• Translate customer needs and operational challenges into ML solutions and product capabilities.
• Provide technical leadership during customer demonstrations, field trials, and critical deployments.
• Serve as the organization’s machine learning subject matter expert.
• Lead and mentor a high-performing machine learning team.
• Establish project priorities, resource allocation, and development plans.
• Drive project execution through planning, risk management, and Jira.
• Define engineering processes, conduct technical reviews, and promote knowledge sharing.

Requirements

• Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Physics, or a related field.
• 5–10 years of experience in machine learning, AI, and software development.
• Experience with AWS.
• Experience with Claude.
• Ability to write in C for embedded systems.
• Proficiency in Python and scripting.
• Ability to convert algorithms to code and apply machine learning concepts such as decision trees, logistic regression, and Bayesian analysis to complex datasets.
• Proven track record leading machine learning teams and delivering quality products.
• Experience with embedded ML on hardware or IoT devices.
• Experience translating real-world applications and customer needs into ML solutions.
• Strong proficiency in Python, including PyTorch and Scikit-learn.
• End‑to‑end ML project experience covering data pipelines, data cleaning, preprocessing, model design, training, validation, and deployment.
• Experience with project management tools, including JIRA.
• Experience with cloud platforms such as AWS or Azure.
• Strong technical communication, documentation, and organizational skills.

Core Competencies

Demonstrates expertise in machine learning strategy, architecture design, and MLOps practices, with a strong focus on model performance optimization and data pipeline management. Proven ability to lead high‑performing teams and translate customer needs into effective ML solutions.

Highest‑signal resume keywords

• Machine Learning Strategy
• MLOps Practices
• Python Proficiency
• Embedded Systems Development
• Project Management with JIRA

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Signal Processing
• Model Selection
• Data Pipeline Management
• Algorithm Development
• C Programming
• Decision Trees
• Logistic Regression
• Bayesian Analysis
• Data Cleaning

Soft Skills

• Technical Leadership
• Organizational Skills
• Technical Communication
• Mentoring
• Collaboration

Industry Keywords

• Machine Learning Models
• Data Governance
• Embedded ML
• IoT Devices
• Field Data Collection

Tools & Technologies

• AWS
• Azure
• JIRA
• PyTorch
• Scikit-learn