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Founding Machine Learning Engineer Jobs in Edmonton, AB

Takeaway

Senior Machine Learning Engineer

Edmonton, AB · On-site

As a Senior ML Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement.

NavitasPartners

MLOps Engineer (BFSI) - MLEBAS

Leduc, AB · On-site

$30/hr

The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models. Key Responsibilities: * Build ML deployment ...

TELUS

L4 Technical Professional

Edmonton, AB · On-site

You will work closely with a team of data scientists and data engineers to deploy solutions and drive innovation using machine learning and NLP techniques. The ideal candidate has a deep ...

TELUS

Senior Data Analyst (L4)

Edmonton, AB · On-site

GCP Professional Machine Learning Engineer Certification * Working knowledge of leveraging Claude in the workflows * Experience with Google Vertex AI or Kubeflow for ML orchestration * Background in ...

TELUS

Staff Applied AI/ML Scientist

Edmonton, AB

Expertise in machine learning frameworks such as TensorFlow, Pytorch, and Keras * Strong understanding of software and AI development lifecycles, with experience in DevOps and MLOps practices

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Founding Machine Learning Engineer information

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
Founding Machine Learning Engineer jobs near you

Machine Learning Engineer (Energy) - MLEEAS

NavitasPartners

Edmonton, AB • On-site

$30/hr

Other

Posted 21 days ago

Job description

Job Title : Machine Learning Engineer (Energy)Industry

Energy & Utilities

Position Overview

The ML Engineer will develop and deploy machine learning models supporting predictive maintenance, energy demand forecasting, asset optimization, and renewable energy production analytics.

Responsibilities
  • Develop machine learning pipelines.
  • Build predictive analytics solutions.
  • Deploy ML models into production.
  • Optimize model performance and monitoring.
  • Collaborate with data scientists and engineers.
  • Support AI-driven operational excellence programs.
Required Skills
  • Python
  • Machine Learning
  • TensorFlow
  • PyTorch
  • Scikit-Learn
  • Databricks ML
  • Feature Engineering
  • Model Deployment
Preferred Skills
  • Predictive Maintenance
  • Demand Forecasting
  • Energy Load Optimization
  • Renewable Energy Analytics
Mandatory Experience
  • 5+ years in Machine Learning Engineering.
  • Must have prior Energy sector experience.


For more details reach at resumes@navitassols.com

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