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Artificial Intelligence Machine Learning Engineer Jobs in Calgary, AB

Java Developer

Calgary, AB ยท Hybrid

CA$80K - CA$90K/yr

... Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering ... learning and development programs, and more. All employment decisions at Synechron are based on ...

... intelligence layer of Tackle's platform - turning machine learning models into real product ... a small engineering team. What we're looking for * 2+ years of professional experience building ...

Systems Developer Company Overview Stream Systems (www.streamsystems.ca) is a leading-edge ... Our SimOpti intelligence platform brings AI, machine learning and simulation to power business ...

As our global expert network grows, micro1 is building the human intelligence layer for frontier AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

As our global expert network grows, micro1 is building the human intelligence layer for frontier AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Associate Analog Design Engineer

Calgary, AB ยท On-site

CA$70K - CA$75K/yr

Additional professional development opportunities include a mix of virtual learning, in-person ... We may leverage Artificial Intelligence (AI) tools to enhance efficiency during candidate screening ...

Associate Analog Design Engineer

Calgary, AB ยท On-site

CA$70K - CA$75K/yr

Additional professional development opportunities include a mix of virtual learning, in-person ... We may leverage Artificial Intelligence (AI) tools to enhance efficiency during candidate screening ...

Showing results 41-60

Artificial Intelligence Machine Learning Engineer information

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Calgary, AB look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Calgary, AB are:

Software Engineer, ML Infrastructure

Serve Robotics

Calgary, AB โ€ข Remote

$155K - $190K/yr

Full-time

Re-posted 13 days ago


Job description

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

As a Software Engineer on the Machine Learning (ML) Infrastructure team, you will help design, build, and maintain our petabyte-scale data and ML platform that powers data partnerships, ML research, and autonomy engineering. You will build and improve our data discovery capabilities and integrate with 3rd party annotation platforms. By collaborating with members of the autonomy and ml teams you will help us refine how we organize various data attributes and classifications. This role plays a pivotal role in helping the team leverage data from our rapidly expanding fleet of thousands of robots.

Responsibilities
  • Develop and maintain highly scalable data processing pipelines for data curation, annotation, search and ml feature extraction.

  • Build data discovery features for the platform.

  • Create and maintain search features such as natural language querying

  • Develop and maintain our orchestration and scheduling systems.

  • Maintain and evolve our data schemas such as unified data attribute system, scenario tagging and management

  • Build integrations with annotation providers to efficiently review large scale data preannotations

  • Collaborate with autonomy engineers to collect feedback, improve documentation, and run tutorials on platform features

Qualifications
  • BS or MS in computer science with focus in data engineering and/or machine learning

  • 3+ years of industry experience building, running and improving large-volume data processing, feature extraction, data annotation workflows

  • Experience building data mining and search capabilities

  • Experience with both Python and SQL is required

  • Solid understanding of data distributions and their impact on ML Models

  • Hands-on experience and good understanding of LLMs, VLMs, embeddings, vector databases

  • Experience with data annotation providers such as CVAT, LabelBox, LabelStudio, etc

What Makes You Stand Out
  • Experience with integrating cloud inference platforms for LLMs/VLMS (ChatGPT, Gemini, etc)

  • Experience working with Multi Modal data (Lidar, Camera, etc)

  • Experience with robotics systems

  • Experience optimizing large scale vector databases

Compensation Range: $155K - $190K