US Mobile is on a mission to revolutionize connectivity. Imagine a world where
you can go into a single app and buy terabytes of data for every one of your
devices: phone, smart devices, car, home broadband, and more. That’s the future
that US Mobile is building: a software platform built truly for the 21st century
and the age of 5G and IoT, with world class engineering, best-in-class user
experience, and features that will define the next generation of connectivity.
At the core of it all, we have a team and culture that has been recognized by
Forbes as one of the top 500 best startup employers in the US. Our team spans
diverse backgrounds, cultures, and stories, with employees coming from 20+
countries.
We're a venture-backed company entering hypergrowth, having recently ranked 94th
on Inc 5000's fastest-growing private companies in America, and we’re looking
for someone exceptional to join our team.
Job Description:
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.
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Key Responsibilities:
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Design & Deploy Conversational / Multi-Agent LLM Solutions
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Craft multi-agent conversational flows capable of handling a wide range of
user requests—both purely informational and action-oriented.
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Employ advanced LLM techniques (prompt engineering, context retrieval,
multi-step reasoning) to ensure robust, context-aware dialogues
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Multi-Modal & Multi-Model Integration
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Explore different input/output formats (e.g., text, potential voice or
image-based flows) to enrich user interactions
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Evaluate different models based on their intended use case, considering both
technical capabilities and cost efficiency
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Platform & Pipeline Building
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Work with cross-functional teams to design data pipelines that feed your
models real-time or near real-time data
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Implement best practices around model lifecycle management—versioning,
containerization, deployment orchestration, etc
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Optimization & Scale
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Ensure the chat system can handle thousands (eventually millions) of
concurrent interactions, maintaining low latency and high availability
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Monitor performance, define metrics (latency, user success rate, fallback
rate, etc.), and iteratively improve
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Ongoing Innovation & Experimentation
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Remain current on the rapidly evolving AI/ML landscape, especially in
generative models, multi-agent orchestration, and knowledge retrieval
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Propose new ways to extend AI across our platform—e.g., advanced
personalization, proactive customer engagements, etc.
Qualifications:
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Core AI/ML Expertise
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3+ years hands-on experience building and deploying machine learning
solutions at scale
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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
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Backend & Data Infrastructure
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Proficient in Python or a similar language for data pipelines and model
development
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Experience with cloud platforms (AWS strongly preferred), containerization
(Docker, Kubernetes), and microservices
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Research & Problem-Solving Mindset
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Up-to-date on AI/ML trends—especially in multi-agent systems, generative
modeling, or multi-modal approaches
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Skilled at diagnosing bottlenecks, scaling solutions, and balancing
innovation against real-world constraints
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Collaboration & Communication
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Comfortable presenting complex ML concepts to non-technical stakeholders
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Passion for iterative development—able to pivot based on user feedback and
product metrics.
Bonus Points:
- Familiarity with vector search solutions (e.g. Pinecone, Weaviate, or
Elasticsearch with vector plugins)
- Familiarity with building or deploying large language models and related
tooling in the AWS Bedrock ecosystem
- Experience designing or contributing to multi-agent LLM frameworks or
orchestrations (e.g., specialized agent-based approaches in advanced NLP)
Benefits:
- Competitive salary 150k CAD - 240k CAD (based on experience)
- Flexible working hours
- Supplemental health insurance
- Professional development stipend
- $500 wfh tech set-up reimbursement
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$150,000 - $240,000 a year
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Think you’d be a great fit? Apply to learn more!
