Senior Machine Learning Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇨🇦 Canada – Remote

💵 $200k - $250k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Numa

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2019

🏨 Hospitality

✈️ Travel

Hospitality • Travel

Numa is a European hospitality brand that operates digitally managed rooms and apartments in city-center locations across Europe. It emphasizes easy, app-driven, keyless check-in and tailored stays for both business and leisure travelers, supporting short and long stays, group and corporate bookings, and offering a membership program with discounts and perks plus 24/7 support. Numa markets properties in many major European cities and focuses on streamlined, contactless guest experiences and business travel services.

📋 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