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Ai Algorithm Engineer Jobs in Burnaby, BC (NOW HIRING)

... AI teams that bring together product leaders, machine learning engineers, and full-stack builders ... Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms ...

Design and develop algorithms for generative models using deep learning techniques. * Collaboration: Work with cross-functional teams to integrate generative AI solutions into existing systems.

While our ML Engineers focus on building, training, and optimizing foundational algorithms, your ... Sitting at the intersection of AI capabilities, enterprise platforms, and human workflows, you will ...

Description As an Applied AI Software Engineer at Photonic, you will play a key role in identifying ... Our hiring decisions are made by people, not algorithms. We are committed to fostering, cultivating ...

About the Role As an AI Engineer in Agent Factory, you'll design and build the core ML systems ... Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms ...

Engineering, but brighter. About the Role As a Principal AI Engineer in Agent Factory, you'll ... Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms ...

Execute ML/AI engineering tasks including exploratory data analysis, data preparation, model ... Solid understanding of ML algorithms, statistics, model evaluation techniques, and feature ...

Senior System Development Engineer

Vancouver, BC ยท On-site

CA$120K - CA$160K/yr

... AI algorithms. Our solutions power key products from Motorola's leading brands including Avigilon ... As a System Development Engineer, you sit at the high-velocity intersection of Software Engineering ...

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Ai Algorithm Engineer information

What is an AI algorithm engineer?

AI Algorithm Engineers are professionals who design, develop, and optimize algorithms that enable artificial intelligence systems to learn from data and perform complex tasks. They work with machine learning, deep learning, and other AI techniques to create models that can analyze information, make predictions, or automate processes. AI Algorithm Engineers often collaborate with data scientists and software developers to implement and improve AI solutions for various industries, such as healthcare, finance, and technology. Their work involves both theoretical research and practical application, requiring strong programming and mathematical skills.

What are the key skills and qualifications needed to thrive as an AI algorithm engineer?

To thrive as an AI Algorithm Engineer, you need strong expertise in mathematics, programming (especially Python, C++, or Java), and a solid background in computer science or a related field, often supported by a relevant degree. Familiarity with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and sometimes certifications in AI or data science are typically required. Creative problem-solving, strong analytical thinking, and effective communication are crucial soft skills that set top candidates apart. These skills and qualifications are essential for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technical environments.

What are some common challenges AI algorithm engineers face when deploying models to production environments?

AI Algorithm Engineers often encounter challenges such as ensuring model scalability, maintaining inference speed, and handling the integration of models with existing systems. Additionally, they must address issues like model drift, data pipeline inconsistencies, and the need for continuous monitoring to maintain accuracy over time. Effective collaboration with data engineers, software developers, and DevOps teams is essential for successful deployment and ongoing model performance.

What is the difference between Ai Algorithm Engineer vs Data Scientist?

AspectAi Algorithm EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; knowledge of algorithms and programmingBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and optimizes AI algorithms, often in R&D or product teamsAnalyzes data, builds models, and provides insights for business decisions
Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

While both roles require strong technical skills and a background in data or algorithms, Ai Algorithm Engineers focus on designing and improving AI algorithms, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap but serve different primary functions within organizations.

Is an AI Algorithm Engineer still in demand?

AI Algorithm Engineers are currently in high demand due to the rapid growth of artificial intelligence applications across industries such as technology, healthcare, and finance. Skills in machine learning, deep learning, and programming languages like Python or TensorFlow are highly valued, and the role often requires staying updated with the latest research and tools. Employment prospects remain strong as organizations continue to invest in AI innovation and automation.

What is the salary of AI Algorithm Engineer?

The salary of an AI Algorithm Engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can earn higher compensation, often exceeding $180,000.
Infographic showing various Ai Algorithm Engineer job openings in Burnaby, BC as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 60% Physical, 3% Hybrid, and 37% Remote job distribution.

Compiler Engineer - Algorithmic Workloads Compilation

Vancouver, BC โ€ข On-site

Full-time

Re-posted 27 days ago


Job description

About us
Mythic is building the future of AI computing with breakthrough analog technology that delivers 100 the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 C to +125 C, making it ideal for industrial, automotive, aerospace, and defense.

We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

About the role
Help push the boundaries of what can run on our accelerator. You'll design compiler IRs and lowering strategies to support algorithmic workloads with irregular or dynamic control flow-loops, branches, and iterative methods-going beyond static neural networks. Working side by side with hardware engineers, you'll influence ISA and execution model co-design to unlock new algorithm classes on analog and digital subsystems. The result: a compiler that makes complex algorithms practical to deploy while staying seamless for developers.
Here's what you will do
  • Extend compiler IRs to represent algorithms not easily captured in DNN graphs including control flow and iterative computation
  • Develop compilation strategies that unify analog compute with digital subsystems while maintaining performance and correctness
  • Prototype and optimize algorithms with irregular or dynamic control flow in compiler IRs, applying techniques such as vectorization, predication, and scheduling
  • Collaborate with hardware engineers to co-design ISA and features that improve support for algorithmic workloads
  • Define a roadmap for higher-level programming abstractions that simplify prototyping and accelerate deployment
Here's the background we hope you will have
  • 3+ years of professional experience in compilers or high-performance systems software
  • Proficiency in modern C++ (C++14/17/20) and Python
  • Familiarity with compiler IRs (e.g., MLIR, LLVM, or equivalent) and their use representing complex program structures
  • Solid foundation in program analysis and optimization techniques (e.g., SSA form, loop optimizations, vectorization)
The following would be nice to have, but is not required
  • Hands-on experience developing MLIR or LLVM dialects for control flow (e.g. scf, cf) or affine/polyhedral representations.
  • Background in compiler-hardware co-design: working with hardware designers to refine ISA or execution models for efficiency
  • Proven ability to prototype irregular or control-flow algorithms in compiler IRs and optimize them for performance and resource constraints
  • Experience extending ML compiler stacks (ONNX, IREE, XLA, PyTorch, TVM) to support workloads beyond DNNs
What we offer
  • The opportunity to make algorithmic and control-flow-heavy workloads practical on novel accelerator hardware.
  • A role that bridges compiler design and hardware co-design, shaping both the IR and the accelerator architecture.
  • A collaborative, innovative team that values engineering rigor, continuous integration, and user-focused design.
  • Competitive compensation, equity, and benefits package.
At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.
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