The AI/ML Engineer will develop and optimize machine learning models, focusing on conversational systems, multi-agent solutions, and scalability, while collaborating across teams to enhance user experiences.
US Mobile is building the future of wireless communication. The goal: one unified network open to any person and any device, worldwide. Connection without walls.
We’re getting there by empowering customers. All three major networks on one phone and one plan, plus home internet from Starlink. No lock-in. No commitments. Custom fit plans at every price point. 24/7 customer support with real people, empowered to help. We get real-time feedback from Reddit, surveys, and customer support informing product roadmaps and everything we do. It’s working — Consumer Reports named us the top-rated mobile carrier two years in a row.*
And we’re building innovative systems that scale. A network agnostic tech stack. Agile, cross-functional teams built on trust and mutual respect. This work isn’t for everyone. If you work fast, flexibly, and collaboratively — without compromising standards — we want to hear from you.
We’re looking for an AI/ML Engineer who will develop, optimize, and scale machine learning models that power our next generation of user experiences. Working closely with product, engineering, and design, you’ll ensure our ML tools truly address user needs—whether they’re discovering new features, troubleshooting connectivity, or receiving proactive solutions to common issues.Key Responsibilities:
- Craft multi-agent conversational flows capable of handling a wide range of user requests—both purely informational and action-oriented.
- Employ advanced LLM techniques (prompt engineering, context retrieval, multi-step reasoning) to ensure robust, context-aware dialogues.
- Explore different input/output formats (e.g., text, potential voice or image-based flows) to enrich user interactions.
- Evaluate different models based on their intended use case, considering both technical capabilities and cost efficiency.
- Work with cross-functional teams to design data pipelines that feed your models real-time or near real-time data.
- Implement best practices around model lifecycle management—versioning, containerization, deployment orchestration, etc.
- Ensure the chat system can handle thousands (eventually millions) of concurrent interactions, maintaining low latency and high availability.
- Monitor performance, define metrics (latency, user success rate, fallback rate, etc.), and iteratively improve.
- Remain current on the rapidly evolving AI/ML landscape, especially in generative models, multi-agent orchestration, and knowledge retrieval.
- Propose new ways to extend AI across our platform—e.g., advanced personalization, proactive customer engagements, etc.
Design & Deploy Conversational / Multi-Agent LLM Solutions
Multi-Modal & Multi-Model Integration
Platform & Pipeline Building
Optimization & Scale
Ongoing Innovation & Experimentation
Qualifications:
- 3+ years hands-on experience building and deploying machine learning solutions at scale.
- Solid understanding of NLP techniques, including transformer models and embeddings, with hands-on experience using modern tools like Hugging Face, AWS Bedrock, and OpenAI’s API.
- Experience with vector search solutions (e.g. Pinecone, Weaviate, or Elasticsearch with vector plugins).
- Experienced in building or deploying large language models and related tooling in the AWS Bedrock ecosystem.
- Familiarity with multi-agent LLM frameworks or Orchestrations (e.g., specialized agent-based approaches in advanced NLP).
- Proficient in Python or a similar language for data pipelines and model development.
- Experience with cloud platforms (AWS strongly preferred), containerization (Docker, Kubernetes), and microservices.
- Up-to-date on AI/ML trends—especially in multi-agent systems, generative modeling, or multi-modal approaches.
- Skilled at diagnosing bottlenecks, scaling solutions, and balancing innovation against real-world constraints.
- Comfortable presenting complex ML concepts to non-technical stakeholders
- Passion for iterative development—able to pivot based on user feedback and product metrics.
Core AI/ML Expertise
Backend & Data Infrastructure
Research & Problem-Solving Mindset
Collaboration & Communication
Benefits:
- Competitive salary - 130k CAD - 220k CAD (based on experience/location)
- Flexible working hours
- Supplemental health insurance
- Professional development stipend
- $500 wfh tech set-up reimbursement
Think you could be a fit? Apply to learn more!
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