Senior Deep Learning Engineer developing player - tracking, evaluation, and forecasting models for SumerSports’ football intelligence platform. Driving research threads into production for NFL and NCAA teams.
About the role
- AI/ML Engineer developing, optimizing, and scaling machine learning models for US Mobile’s next-gen user experiences. Collaborating with teams to enhance connectivity through innovative solutions.
Responsibilities
- Design & Deploy Conversational / Multi-Agent LLM Solutions
- 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.
Requirements
- 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 to 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.
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
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