Salary: $170,000 – $200,000 per year

Remote: Remote

170,000 - $200,000 CADThe salary range listed reflects the base pay for this role at Altus Group and is provided where required by local regulations. The range does not include additional compensation such as bonuses, equity, benefits, or other incentives.This role will lead the design, development, and production deployment of advanced AI and machine learning capabilities across a commercial real estate SaaS platform. The position combines hands‑on technical leadership with applied research, building both LLM‑powered features and custom domain‑specific models. The role partners closely with engineering, product, data, and architecture teams to translate complex business problems into scalable AI solutions, while establishing standards, infrastructure, and best practices for AI development across the organization.Architect and implement AI-powered features across the SaaS platform, including agentic workflows, intelligent data extraction, and analysis capabilities Lead research and development of custom AI/ML models tailored to the commercial real estate domain Evaluate fine‑tuning foundation models versus building domain‑specific models from scratch Establish technical standards, patterns, and best practices for AI/ML development across feature teams Lead hands‑on development of complex AI systems, including LLM integrations, RAG architectures, and multi‑agent orchestration Design and implement model training pipelines, experiment tracking, and model versioning infrastructure Make build‑versus‑buy decisions for AI tooling and frameworks, balancing innovation with pragmatism Design scalable infrastructure for AI workloads, including model serving, inference optimization, and GPU resource management Partner with engineering and architecture leaders to identify AI opportunities and guide implementation Collaborate with Platform, Data, and Analytics teams to ensure access to high‑quality, unified data Work with product managers to translate business requirements into technical AI solutions Mentor engineers on AI/ML techniques, prompt engineering,



and agentic frameworks Drive the technical roadmap for AI capabilities across applied LLM work and custom model development Lead research initiatives advancing CRE‑specific AI applications Champion AI adoption through internal knowledge‑sharing initiatives such as the AI Guild Evaluate emerging AI technologies and research, leading proofs‑of‑concept where appropriate Establish experimentation frameworks for rapid iteration and A/B testing of AI features Contribute to the AI/ML community through publications, blogs, or open‑source work Define governance models, quality gates, testing strategies, and safety measures for AI systems Create documentation and runbooks to support reliable operation of AI‑powered features Balance rapid innovation with responsible AI practices and risk management 8+ years of product engineering experience, with at least 3 years focused on production AI/ML systems Proven experience training, evaluating, and deploying custom ML models in production environments Hands‑on experience with both LLM‑powered applications and traditional ML model development Deep understanding of model architectures, training methodologies, and optimization techniques Strong software engineering fundamentals, including system design, APIs, and cloud architectures Experience leading technical initiatives across teams or operating at staff or tech lead level Active hands‑on coder with ongoing experience writing production code and training models Publication record (academic papers, patents, or significant open‑source contributions) is a strong plus Expert‑level knowledge of ML fundamentals, including neural networks, transformers, and optimization algorithms Proficiency with distributed training, GPU optimization, and experiment tracking tools Strong foundation in statistics, probability,



and mathematical optimization Experience with advanced ML architectures such as transformers, diffusion models, graph neural networks, or reinforcement learning Knowledge of vector databases, embeddings, and semantic search technologies Experience in data engineering for ML, including feature stores, data pipelines, and data quality practices Understanding of MLOps practices such as model monitoring, A/B testing, shadow deployments, and versioning Cloud experience (AWS, Azure, or GCP) supporting ML workloads at scale Strong technical communication skills with ability to explain complex concepts to diverse audiences Our high trust, high performance culture prioritizes progressive programs that empower you to deliver your greatest performance while promoting collective success where everyone is recognized and connected.We offer boundless opportunities in a rapidly growing global business: mentorship from the best and brightest in CRE, access to our Altus Intelligence Academy, and the chance to work with the best data sets, tools and technology in the industry.Rewarding performance: competitive compensation, incentive and bonus plans, and a total rewards package prioritizing mental, physical, and financial well‑being. Our Altus Intelligence Academy offers over 150,000 hours of learning content. Flexible work model: our Activity-Based Work model provides flexibility to align your work location to the needs of the work — use the office for collaboration and work from home for focused tasks. We provide an atmosphere free from barriers to promote diversity, equity, and inclusion, and encourage equal opportunities for all employees. Use of Artificial Intelligence AI tools may be used to support the initial stages of screening for this role; These checks may include, but are not limited to, verification of employment history, education credentials, criminal records, credit history (where relevant), and reference checks. All background checks will be conducted in compliance with local laws and regulations, and candidates will be informed of any checks required as part of the recruitment process.

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