Multidisciplinary Engineer

OUR STORY

TechInsights is the information Platform for the semiconductor industry.

Regarded as the most trusted source of actionable, in-depth intelligence related to semiconductor innovation and surrounding markets, TechInsights’ content informs decision makers and professionals whose success depends on accurate knowledge of the semiconductor industry—past, present, or future.

Over 650 companies and 150,000 users access the TechInsights Platform, the world’s largest vertically integrated collection of unmatched reverse engineering, teardown, and market analysis in the semiconductor industry. This collection includes detailed circuit analysis, imagery, semiconductor process flows, device teardowns, illustrations, costing and pricing information, forecasts, market analysis, and expert commentary. TechInsights’ customers include the most successful technology companies who rely on TechInsights’ analysis to make informed business, design, and product decisions faster and with greater confidence. For more information, visit .

WHY WORK WITH US

• Company-sponsored training and development opportunities
• Comprehensive benefits package (health, dental, vision, wellness, RRSP/401K Matching, annual fitness reimbursement)
• Flexible vacation policy
• Bring your own device program
• Wellness resources and support
• Inclusive environment that prioritizes diversity, equity, and accessibility
• High-growth company driven by high performance

Expected salary range: $88,000 - $93,000 CAD

THE OPPORTUNITY:

The TechInsights Research & Development team is seeking a multidisciplinary engineer who thrives at the intersection of cloud operations, scientific software development, and applied AI research. This unique hybrid role splits time between DevOps/Scientific Python development and AI/ML research for big data and image processing. You'll bridge R&D innovations into scalable production environments, working on cutting-edge technology while maintaining production-grade engineering standards.

WHAT YOU’LL DO

Scientific Python Engineering & Kimera Integration

• Translate research prototypes into production-grade modules for integration into Kimera, our cloud-based production processing platform
• Work closely with R&D team members to evaluate, refine, and deploy new algorithms
• Develop automation scripts and tooling to streamline scientific workflows
• Ensure code quality, performance, reliability, and documentation standards appropriate for a production environment

DevOps & Cloud Operations

• Maintain and optimize AWS cloud infrastructure (EC2, S3, Lambda, ECS/EKS)
• Manage CI/CD pipelines ensuring automated testing, validation, and deployment (Bitbucket Pipelines or similar)
• Operate and troubleshoot Kubernetes clusters (EKS), including Helm chart management and cluster lifecycle tasks
• Develop and maintain infrastructure-as-code using Terraform or CloudFormation
• Provide production support for Linux-based cloud environments
• Monitor system health using tools such as Datadog, CloudWatch, or Grafana
• Collaborate with internal teams to ensure stable, scalable deployments of Kimera and related services

AI/ML & Image Processing Research

• Conduct applied research in AI/ML methods for big-data processing, computer vision, and image analytics
• Prototype new models, algorithms, and data pipelines using frameworks such as PyTorch or TensorFlow
• Design experiments, analyze results, and iterate on research hypotheses
• Evaluate state-of-the-art methods and determine feasibility for integration into production
• Present findings internally and contribute to technology roadmaps

WHAT YOU’LL BRING

• A Bachelor’s Degree or equivalent experience in Computer Science or related fields.
• A problem-solving, research-oriented mindset with the ability to move between exploratory and production contexts
• Strong Python skills, especially in scientific computing (NumPy, SciPy, Pandas) and software engineering best practices
• Experience with AI/ML frameworks (TensorFlow, PyTorch) and image processing libraries (OpenCV, scikit-image, etc.)
• Background in computational imaging, signal processing, or applied machine learning
• Experience integrating research algorithms into cloud-native production systems
• Ability to support users, diagnose issues, and collaborate cross-functionally
• Linux user-level skills

Considered an Asset:

• Linux system administration skills in cloud environments
• Experience with AWS cloud services (EC2, S3, Lambda, ECS/EKS)
• Kubernetes (EKS), Helm and cluster management experience
• Familiarity with big-data processing workflows and distributed systems
• Experience with system mon