Rwazi Logo

Rwazi

Research Engineer

Posted Yesterday
Be an Early Applicant
In-Office or Remote
Hiring Remotely in Canada
Mid level
In-Office or Remote
Hiring Remotely in Canada
Mid level
Build and maintain experimental decision-system prototypes, evaluation tooling, simulation environments, and research infrastructure to enable rapid iteration and validation of research concepts in real-world constraints.
The summary above was generated by AI
Research Engineer

Team: Research & Development
Location: Flexible / Remote
Reporting to: Head of R&D

Role Overview

Rwazi’s research initiatives require rapid experimentation, prototyping, and system validation.

The Research Engineer enables applied research through technical system construction.

This role builds prototypes, experimental pipelines, evaluation tooling, and research infrastructure that allow decision concepts to be tested under real-world constraints.

The Research Engineer operationalizes research velocity.

Core Mandate

The Research Engineer is accountable for:

  • Building research prototypes and sandbox environments

  • Developing evaluation tooling for decision systems

  • Implementing experimental system architectures

  • Enabling fast iteration between theory and validation

  • Maintaining technical research infrastructure

This role bridges conceptual research and system reality.

Key ResponsibilitiesPrototype Development
  • Implement experimental decision pipelines

  • Build modular, testable research architectures

  • Translate conceptual models into runnable systems

Research Tooling & Infrastructure
  • Create evaluation frameworks for reasoning outputs

  • Build simulation environments for controlled testing

  • Develop benchmarking systems for decision performance

Experiment Enablement
  • Implement A/B logic and structured experiment tracking

  • Optimize iteration cycles for research testing

  • Ensure reproducibility of experimental results

System Integration Support
  • Collaborate with Decision Research Scientists to encode models

  • Provide technical validation of research concepts

  • Identify engineering constraints early

Role Impact

Strong performance in this role results in:

  • Faster research iteration cycles

  • More reliable prototype validation

  • Reduced gap between research and production

  • Higher experimental rigor

This role accelerates Rwazi’s long-term capability development.

What This Role Is Not
  • This is not product feature engineering

  • This is not maintenance development

  • This is not short-term optimization

This role builds experimental systems.

Qualifications and Profile

We are looking for individuals who demonstrate:

  • Strong software engineering fundamentals

  • Experience building experimental or prototype systems

  • Comfort working in ambiguous research environments

  • Ability to balance speed and technical rigor

  • Familiarity with AI pipelines or decision architectures

Candidates may come from research labs, AI startups, advanced analytics teams, or system architecture roles.

How Candidates Are Evaluated

Candidates are evaluated based on:

  • Their ability to rapidly implement experimental systems

  • Technical clarity and modularity of their code

  • Comfort working with incomplete specifications

  • Understanding of evaluation logic and system validation

  • Ability to collaborate with research-oriented thinkers

Summary

The Research Engineer enables Rwazi’s applied decision research by building the technical infrastructure required to explore, validate, and evolve next-generation decision systems.

If you'd like, we can next define:

  • Decision Systems Fellow (elite individual contributor track)

  • AI Evaluation & Alignment Lead

  • Advanced Simulation Architect

  • Future Platforms Lab

Similar Jobs

Yesterday
Remote
Canada
Senior level
Senior level
Healthtech • Software
Build and own a versioned, documented gold data layer from lakehouse silver tables for AI research. Transform, validate, and productize multi-modal datasets and pipelines (Databricks/PySpark) to support model development, evaluation, and production ML/LLM workflows while ensuring data quality, provenance, and regulatory controls.
Top Skills: AirflowAsrAWSAzureCcdaCi/CdDagsterDatabricksDatabricks WorkflowsDbtDelta LakeFeature StoreFhirGitHl7V2Hugging Face DatasetsIcd-10Llm ApiLoincLshMinhashMlflowOcrParquetPrefectPysparkPythonPyTorchSnomed CtSnorkelSparkSQLUnity Catalog
14 Days Ago
Remote or Hybrid
CA
Mid level
Mid level
Artificial Intelligence • Enterprise Web • Machine Learning • Software
Build tools and infrastructure for training language and multi-agent models in interactive environments; research and implement advances in language modeling and reinforcement learning; contribute to publications and open-source projects.
Top Skills: AWSAws LambdaGpusPythonPyTorch
15 Days Ago
Remote or Hybrid
CA
Mid level
Mid level
Angel or VC Firm • Artificial Intelligence
Research and build efficient ML systems for large-scale LLMs and agentic RL: design algorithms and system techniques, prototype in training/inference stacks, run large-scale experiments, and translate findings into production or publications.
Top Skills: Attention MechanismsDistributed TrainingHugging FaceJaxPythonPyTorchReinforcement LearningTransformers

What you need to know about the Vancouver Tech Scene

Raincouver, Vancity, The Big Smoke — Vancouver is known by many names, and in recent years, it has gained a reputation as a growing hub for both tech and sustainability. Renowned for its natural beauty, the city has become a magnet for professionals eager to create environmental solutions, and with an emphasis on clean technology, renewable energy and environmental innovation, it's attracted companies across various industries, all working toward a shared goal: advancing clean technology.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account