Solutions Architect, AI/ML

Fidus Systems

. Work directly with potential and existing clients to understand their needs and develop requirements .

Posted 10/28/2026full-timeRemote • CanadaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI/ML engineering with a strong focus on system-level design, deployment of machine learning models, and architectural decision-making. Proficient in collaborating across multidisciplinary teams while ensuring compliance with ITAR and CGP regulations.

Highest-signal resume keywords

AI/ML EngineeringSystem-Level DesignMachine Learning ToolchainEmbedded Software DeploymentConcise Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML EngineeringSystem-Level DesignMachine Learning ToolchainCUDAROCmFPGA DeploymentInference DeploymentQuantizationPruningData Pipeline Assessment

Soft Skills

Concise CommunicationListening SkillsUnderstanding SkillsPresentation SkillsPersonable Interaction

Tools & Technologies

PyTorchTensorFlowONNXMLOpsHigh-Speed InterconnectMemory HierarchyThermal ManagementPower Budgeting

Certifications & Qualifications

Background ChecksSecurity ScreeningSecurity Clearance

Industry Keywords

ITAR ComplianceCGP ComplianceEmbedded SystemsAI AcceleratorsFPGAAdaptive SoC

Tech Stack

Tools & technologies

PyTorchTensorflow

About the role

Key responsibilities & impact

Work directly with potential and existing clients to understand their needs and develop requirements
Architect solutions that meet client needs
Develop plans, identify risks and mitigation strategies, and estimate work required to deliver client solutions
Write technical content for proposals
Present Fidus’ resource capabilities and work approach
Discuss, promote, defend, and refine work approaches and estimates
Evaluate and understand solutions and partition programs into logical segments
Undertake project work as required
Assist in identifying and developing new Fidus products
Assist in identifying new investment and research-and-development areas
Collaborate across FPGA/DSP, hardware, embedded software, verification, SI/PI, PCB layout, and mechanical/thermal design teams

Requirements

What you’ll need

Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent
At least seven (7) years of design background in an AI/ML engineering role is ideally required, with significant time deploying models into production
System-level design experience, including identifying architectural approaches and tradeoffs
Expert knowledge of the modern machine learning toolchain, including PyTorch or TensorFlow, ONNX, quantization, pruning, and compilation for deployment
Experience deploying inference on embedded and accelerated targets such as FPGA and adaptive SoC, GPU, or dedicated AI accelerators
Ability to reason about latency, throughput, power, and memory bandwidth tradeoffs
Experience designing with CUDA and/or ROCm
Familiarity with high-speed interconnect, memory hierarchy, and thermal and power budgets
Ability to assess AI feasibility against available data and scope data pipeline, training, and validation efforts
Some knowledge of FPGAs, hardware, and embedded software
Exposure to MLOps, including model versioning, monitoring, and retraining in production, is an asset
Ability to undertake designs subject to ITAR or classified-information restrictions in the United States, or CGP or classified-information restrictions in Canada
Concise communication and writing skills
Excellent listening, understanding, and extrapolation skills
Professional and personable
Enjoys travel, anticipated to be up to 6 weeks per year, typically within North America
Proven experience giving presentations to small-to-medium-sized groups
Must complete background checks and security screening under Canada’s Controlled Goods Program (CGP); may also need security clearance under the Contract Security Program (CSP)

Benefits

Comp & perks

Comprehensive medical, dental, and vision plans
Matching GRSP contributions
Annual profit-sharing bonus
Other supplementary benefits
Travel opportunities, typically within North America, up to 6 weeks per year