2

Remote Machine Learning Jobs in Edmonton, AB (NOW HIRING)

Manager AI

Edmonton, AB · On-site +1

Deep technical knowledge and 3+ years of experience in deploying AI and machine learning solutions ... Anywhere in Canada (hybrid or fully remote work arrangement) * Collaboration : Work with experts in ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

Collaborate across multiple time zones, ensuring remote teammates are included, unblocked, and aligned. Product Partnership & Business Acumen * Partner with your Product Manager and teammates to help ...

Remote Machine Learning information

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What are the most commonly searched types of Machine Learning jobs in Edmonton, AB? The most popular types of Machine Learning jobs in Edmonton, AB are:
What are popular job titles related to Remote Machine Learning jobs in Edmonton, AB? For Remote Machine Learning jobs in Edmonton, AB, the most frequently searched job titles are:

Junior Machine Learning Engineer - Alerts Team

Samdesk

Edmonton, AB • On-site, Remote

Full-time

Posted 12 days ago


Job description

Who We Are

Samdesk is a global disruption monitoring platform delivering real-time crisis alerts 24 hours a day, 365 days a year, powered by AI. We make sense of the world's most valuable real-time data sources with a singular purpose: to create a safer world. Headquartered in Edmonton, Alberta, Canada, with team members distributed around the globe, we work with some of the largest brands in the world - including DoorDash, Meta, Uber, Ford, and NATO. We are a growing team of builders and problem-solvers who are deeply passionate about the products and services we create.


Check us out!
www.samdesk.io


About the Role

The ML Engineer on the Alerts Team plays a pivotal role in the intelligence layer that powers Samdesk's automated alert pipeline - converting raw unstructured text to actionable crisis intelligence. You will own the quality of the output of our data pipeline. What does this mean? You will own the design and implementation of AI agents, orchestrate the interplay between our LLMs and data pipeline, and build the internal tooling that our operations, ML, and product teams rely on daily. You will work at the intersection of large-scale data systems and cutting-edge AI infrastructure, and your decisions will have a direct impact on system reliability and the quality of alerts delivered to users around the world.


This role reports into the Alerts Team and collaborates closely with features, infrastructure, and product teams.


Responsibilities

Model Development & Fine Tuning

  • Design, build, and deploy ML models across the full lifecycle, from designing the ML architecture through error analysis and deployment
  • Fine-tune and adapt LLMs using domain-specific alert data, including dataset curation, supervised fine-tuning, preference optimization, evaluation, and safe production rollout
  • Upgrade models to newer versions, ensuring each new version measurably outperforms the last
  • Work hands-on with Python ML libraries such as PyTorch, TensorFlow, Hugging Face, and XGBoost
  • Collaborate with data and engineering teams to build scalable ML pipelines
  • Contribute to data labeling strategies, feature engineering, and model evaluation frameworks

AI Agent Development & LLM Orchestration

  • Design and implement AI agents that coordinate LLM inference with our real-time data pipeline
  • Build and maintain the orchestration layer governing how language models interact with structured pipeline outputs
  • Integrate with OpenAI and Anthropic APIs, including prompt engineering, tool use, and response handling at scale
  • Ensure agent workflows are observable, testable, and fault-tolerant in production
  • Monitor and report on model performance, drift, and inference latency in production

Technical Excellence

  • Attention to detail and problem-solving aptitude
  • Set the bar for code and model quality through rigorous review of code, experiments, and evaluation results, and through mentorship
  • Champion reproducibility through experiment tracking, versioned datasets, and robust evaluation so models and systems can be safely iterated on
  • Decompose complex requirements into accurate effort estimates


Qualifications & Skills

Required

  • 2+ years of professional experience in a machine learning or applied ML engineering role
  • Familiarity with NLP, text classification, or information retrieval (a strong asset given our domain)
  • Comfort working with large, noisy, real-world datasets
  • Demonstrated experience building and operating AI agents or LLM-powered systems in production
  • Hands-on experience with OpenAI and/or Anthropic APIs, including tool use, streaming, and prompt management
  • Experience evaluating the outputs of ML components (ie precision and recall)

Nice to Have

  • Experience with real-time data pipelines or event-driven architectures
  • Familiarity with LLM evaluation frameworks, observability tooling, or RAG architectures
  • Background in news, media monitoring, or open-source intelligence (OSINT)
  • Solid working knowledge of AWS services (S3, SQS, CloudWatch) and ML infrastructure such as GPU-based inference, or vector databases

You'll Thrive Here If

  • You bring genuine intellectual ownership to the systems you build and think about them when you're not at your desk
  • You have strong opinions, loosely held. You argue for the right solution, not your solution
  • You have a bias towards action and don't require a 'playbook' to get things done.


Samdesk is an equal opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.


The position is based out of Edmonton, AB but we may also consider remote candidates. Please note that only candidates selected for the interview process will be contacted. Thank you!