Senior Machine Learning Engineer

atNumaRemoteCA flagCanadaFull-timeMachine Learning EngineerSeniorC$200k – C$250k/year

Posted Sep 23

This is a fully remote position, open to applicants in Canada.

πŸ“‹ Description

β€’ Develop conversational AI systems for phone and SMS that comprehend customer requirements, take appropriate actions, and identify when to operate independently.

β€’ Create memory, knowledge graphs, and verified customization tools tailored for dealership-centric agents.

β€’ Train, assess, and implement ML models utilizing Ray Serve and Dagster for tasks such as prediction, classification, ranking, and capacity forecasting.

β€’ Sustain ML models in a production environment.

β€’ Design offline and online evaluations, simulations, and CI gates to gauge quality and identify regressions.

β€’ Establish shared evaluation, observability, and LLM tools.

β€’ Contribute to model serving, LLM infrastructure, and production observability.

β€’ Enhance engineering standards through design and code evaluations, technical documentation, and mentoring.

β€’ Operate independently and assist in clarifying uncertain situations.

β€’ Deliver AI features such as prompts, agents, tools, and production ML models that engage with actual customers.


⛳️ Requirements

β€’ Minimum of 6 years of experience in software or machine learning engineering.

β€’ Proven history of deploying ML or LLM-powered systems in a production setting.

β€’ Proficient in Python with a solid grasp of software engineering principles.

β€’ Practical experience in building AI systems.

β€’ Background in training and deploying ML models for prediction, classification, and ranking, as well as experience with LLMs, prompting, tool utilization, agents, and retrieval.

β€’ Evaluation-first mindset with the ability to measure enhancements and identify regressions.

β€’ Ability to navigate significant ambiguity in a product-driven environment.

β€’ Strong ownership and communication skills to manage projects from problem identification to shipping, monitoring, and improving.

β€’ Nice to have: Experience with ML platforms and tools, including evaluation frameworks, model serving, feature/prompt registries, or ML observability.

β€’ Nice to have: Familiarity with LiveKit, Ray Serve, Dagster, Vertex AI, GCP, Kubernetes, Pulumi, Anthropic, OpenAI, Deepgram, or ElevenLabs.

β€’ Nice to have: Experience with real-time or streaming systems, including voice, SIP/WebRTC, or low-latency inference.

β€’ Nice to have: Background in startup or high-growth environments.


🏝️ Benefits

β€’ Equity Packages

β€’ Flexible PTO

β€’ Fully Covered Group Insurance

β€’ Opportunities for career advancement

β€’ Support for everyone's growth

β€’ Exposure to category-defining AI technology and industry leadership.

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