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Python Ml Developer Jobs in Vancouver, BC (NOW HIRING)

Support AI/ML infrastructure: GPU compute provisioning, model serving, and inference pipelines ... Solid scripting skills (Python, Bash, or Go) * Experience building and maintaining CI/CD pipelines ...

Senior Engineering Manager, AI/ML

Burnaby, BC ยท On-site

CA$200K - CA$250K/yr

{Must be willing to work out of our Vancouver, BC, Canada engineering site}. At Remitly, we believe ... Strong proficiency in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or ...

Senior Machine Learning Engineer

Vancouver, BC ยท On-site

CA$84K - CA$128K/yr

... Azure DevOps. Ability to leverage cloud-native tools to build scalable and secure ML workflows ... Advanced programming skills in Python, with practical experience using popular machine learning ...

Acting as a senior technical partner to product, engineering, and business leaders on AI ... Experience with ML implementation using commonly used tools such as Python, pyTorch, cloud ML ...

Act as a subject-matter expert in AI/ML design discussions, ensuring all customer data is secure ... Possess commercial software development experience with Python, cloud platforms (Google Cloud ...

Job Requisition ID # 25WD94058 25WD94058, Software Architect, AI/ML L'affichage de poste en ... Python/TypeScript/Java with strong engineering fundamentals (testing, code quality, performance ...

Architect and develop AI/ML full-stack solutions and proof-of-concepts using GenAI technologies and ... Frontend (React, modern JavaScript/TypeScript) and Backend (Python, RESTful APIs) * Strong ...

Coach and mentor a growing team of data scientists and engineers, fostering a culture of continuous ... Strong expertise in Python and experience with data science libraries (e.g., Scikit-learn, Pandas ...

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Python Ml Developer information

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
What are popular job titles related to Python Ml Developer jobs in Vancouver, BC? For Python Ml Developer jobs in Vancouver, BC, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Vancouver, BC look for? The top searched job categories for Python Ml Developer jobs in Vancouver, BC are:

DevOps Engineer

iCounter

Burnaby, BC โ€ข Hybrid

Full-time

Posted 4 days ago


Job description

About iCOUNTER

iCOUNTER is building the future of cybersecurity.


Modern enterprises rely on thousands of third parties, suppliers, SaaS providers, contractors, and digital partners. At the same time, attackers have shifted their focus to these trusted relationships. Today, nearly half of reported breaches involve a third party, making the extended enterprise one of the largest attack surfaces in cybersecurity.


iCOUNTER is the first Risk Intelligence company built to help organizations identify, determine, and counter threats across their ecosystem. Our AI-native platform makes a Risk Determination at the point of intelligence collection, helping organizations understand what is real, what is relevant, and what requires action.

At the center of our platform is CTOS, the Counter Threat Operating System. CTOS continuously monitors adversary activity, credential exposure, targeting behavior, and ecosystem risk across third and fourth parties. It then routes intelligence into action through automated workflows and managed operations.


If you want to help define the next era of cybersecurity and build technology that helps organizations stop monitoring threats and start countering them, we'dlove to meet you.


Position Overview

We're looking for a mid-level DevOps Engineer to join our infrastructure team. You'll build and maintain the systems that power our applications and AI/ML workloads, working at the intersection of traditional infrastructure and emerging AI infrastructure. This is a hands-on role for someone who enjoys automation, reliability, and scaling systems that support data-intensive and GPU-accelerated workloads.


This is a hybrid role requiring at least 3 days in office.


Responsibilities

  • Design, deploy, and maintain CI/CD pipelines for application and ML model deployment
  • Manage cloud infrastructure (AWS/GCP/Azure) using Infrastructure as Code
  • Support AI/ML infrastructure: GPU compute provisioning, model serving, and inference pipelines
  • Build and maintain containerized workloads using Docker and Kubernetes
  • Implement monitoring, logging, and alerting for system reliability and observability
  • Collaborate with ML engineers and data scientists to operationalize models (MLOps)
  • Automate infrastructure provisioning and configuration management
  • Participate in on-call rotation and incident response
  • Optimize infrastructure costs, particularly for compute-heavy AI workloads


Requirements

  • 3+ years of DevOps, SRE, or infrastructure engineering experience
  • Proficiency with at least one major cloud provider (AWS, GCP, or Azure)
  • Strong experience with Infrastructure as Code (Terraform, CloudFormation, or Pulumi)
  • Hands-on experience with Docker and Kubernetes
  • Solid scripting skills (Python, Bash, or Go)
  • Experience building and maintaining CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins, etc.)
  • Familiarity with monitoring/observability tools (Prometheus, Grafana, Datadog, etc.)
  • Strong understanding of Linux systems and networking fundamentals


Preferred Qualifications

  • Experience with GPU infrastructure and CUDA-enabled workloads
  • Exposure to ML pipeline and orchestration tools
  • Familiarity with model serving frameworks
  • Understanding of MLOps practices and model lifecycle management
  • Experience with distributed training or large-scale data processing
  • Exposure to vector databases or LLM application infrastructure


Why Join iCOUNTER

This is a rare opportunity to help define a new cybersecurity category while working alongside industry pioneers, experienced operators, and world-class investors. You will have a direct impact on company strategy, market leadership, and the future of how organizations counter threats across their extended enterprise.

If you are energized by ambiguity, inspired by innovation, and excited to build something category-defining, we want to hear from you.


Completion of a Background Check is required for employment at iCOUNTER


iCOUNTER is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. iCOUNTERprovides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act.


Accommodation: If you need accommodations, reach out to accommodations@icounter.com.