Applied Software Engineer

13 hours ago


Ottawa, Ontario, Canada Dominion Dynamics Full time $80,000 - $120,000 per year
Forward Deployed Software Engineer - NLP/AI
Preferred Location: Ottawa
Reports to: CTO

Type: Full-Time

About Dominion Dynamics

Dominion Dynamics is building Canada's first modern defence prime: software-defined, attritable, and sovereign.

We believe tomorrow's military power won't hinge on exquisite platforms, but on the seamless coordination of adaptable, AI-driven capabilities across every domain. We're building that family of systems, fielded with operators, sovereign by design, and accountable to Canada's democratic values.

We move fast, deploy with the CAF, especially in the Arctic, and operate with uncompromising respect for Canadian law, treaty obligations, and the CAF community.

Our founding team includes former operators from Anduril, Google, Amazon, and the Canadian Armed Forces. We're building hard tech in hard places, and we're looking for system-level thinkers who thrive at the intersection of autonomy, aerospace, and national security.

Why This Role Matters

Language and inference capabilities unlock faster decision cycles by extracting, summarizing, and surfacing actionable intelligence from high-volume feeds and operator inputs. This role moves NLP research into resilient, field-ready pipelines that work in constrained, latency-sensitive environments and improve operator effectiveness.

The Role: Forward Deployed Software Engineer - NLP/AI

You will develop and deploy NLP and ML systems that extract, summarize, and contextualize domain data for operators and analysts. This role emphasizes robust model pipelines, performance-conscious inference, and production-grade evaluation to ensure usable outputs in operational settings.

What You'll Do
  • Build and maintain NLP model pipelines for extraction, summarization, classification, and retrieval.
  • Fine-tune and evaluate models using PyTorch/TensorFlow and standard NLP toolkits; implement continuous evaluation.
  • Optimize models for inference on edge or constrained compute, including quantization and latency tuning.
  • Implement data ingestion, labeling, and validation workflows to support model training and monitoring.
  • Integrate NLP outputs with UIs, including Android clients, and backend services for operator-facing workflows.
  • Instrument model performance monitoring and drift detection; iterate on datasets and architectures.
  • Collaborate with systems and software teams to ensure secure, auditable model deployment and operation.
  • Support field validation and refine models based on operational feedback.
What You'll Bring
  • Bachelor's or Master's in Computer Science, Machine Learning, Data Science, or equivalent practical experience.
  • Mid-level: ~2-4 years building and deploying NLP/ML models; experience in production or fielded systems preferred.
  • Strong Python skills and practical experience with PyTorch or TensorFlow.
  • Proficiency with ONNX and model optimization for limited-compute inference, including evaluation and performance monitoring workflows.
  • Practical experience with data pipelines, annotation workflows, and model validation.
  • Mission-oriented, pragmatic problem solver who can support in-field testing and rapid iteration.
  • Eligibility for Canadian security clearance preferred; Canadian citizenship an asset.
Why Join Us

At Dominion Dynamics, we're designing systems that work where others fail, in the most extreme environments on Earth.

At Dominion Dynamics you'll:

  • Shape the future of Canada's sovereign defence.
  • Build real capability in fields with CAF and allies.
  • Move fast, field fast with small teams, high trust, and rapid iteration.
  • Operate with integrity under Canadian law and treaty obligations.
  • Have impact from day one with equity, responsibility, and direct access to leadership.

If you're driven by innovation, adaptability, and the opportunity to make a strategic impact, this is where you belong

Compensation

We offer competitive salary, and meaningful equity participation.



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