Senior Machine Learning Engineer

Job not on LinkedIn

🕒 September 23

🇨🇦 Canada – Remote

💵 $200k - $250k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 6%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Numa

WebsiteLinkedInAll Job Openings

51 - 200 employees

🚘 Automotive

☁️ SaaS

🤝 B2B

💰 $32M Series B on 2024-09

Automotive • SaaS • B2B

Numa is an AI-driven communications and workflow platform for automotive dealerships. It provides Voice AI that answers calls with the customer's full history, an Appointment Agent that books service appointments into real open slots, call intelligence and scoring, precision routing, a smart inbox for calls and texts, and tools to surface declined or unsold opportunities. Numa integrates with major DMS, scheduler, and CRM systems (CDK, Reynolds & Reynolds, Tekion, Dealertrack, Xtime) and is available through OEM programs (GM, FordDirect, Stellantis, BMW), focusing on improving service and sales operations across dealerships.

📋 Description

• Build conversational AI systems for phone and SMS that understand customer needs, take action, and determine when to act autonomously • Develop memory, knowledge graphs, and validated customization tooling for dealership-focused agents • Train, evaluate, and deploy ML models using Ray Serve and Dagster for prediction, classification, ranking, and capacity forecasting • Maintain ML models in production • Create offline and online evaluations, simulations, and CI gates to measure quality and catch regressions • Implement shared evaluation, observability, and LLM tooling • Contribute to model serving, LLM infrastructure, and production observability • Raise engineering standards through design and code reviews, technical writing, and mentorship • Work autonomously and help create clarity in ambiguous situations • Ship AI features including prompts, agents, tools, and production ML models that interact with real customers

🎯 Requirements

• 6+ years of software or machine learning engineering experience • Track record of shipping ML or LLM powered systems to production • Strong Python and solid software engineering fundamentals • Hands-on experience building AI systems • Experience training and deploying ML models for prediction, classification, and ranking and/or working with LLMs, prompting, tool use, agents, and retrieval • Evaluation-first approach and ability to use measurement to assess improvements and regressions • Comfort operating with meaningful ambiguity in a product environment • Ownership and communication skills to carry work from problem framing through shipping, monitoring, and improvement • Nice to have: ML platform and tooling experience, including evaluation frameworks, model serving, feature/prompt registries, or ML observability • Nice to have: Familiarity with LiveKit, Ray Serve, Dagster, Vertex AI, GCP, Kubernetes, Pulumi, Anthropic, OpenAI, Deepgram, or ElevenLabs • Nice to have: Real-time or streaming systems experience, including voice, SIP/WebRTC, or low-latency inference • Nice to have: Startup or high-growth environment experience

🏖️ Benefits

• Equity Packages • Flexible PTO • Fully Covered Group Insurance • Opportunities for career advancement • Everyone's growth • Category-defining AI technology and industry leadership exposure

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