A day in the life
We are seeking a highly motivated and strategic AI & LLM Lead to join our data science team. This individual will be responsible for identifying, designing, and executing AI-driven solutions, with a strong focus on leveraging large language models (LLMs) and generative AI to create transformative applications across business units. This role is ideal for someone who combines deep technical expertise with strong business acumen, and who thrives on building from 0 to 1.
Key Responsibilities Include
- Business Use Case Translation: Collaborate with business leaders to translate strategic goals into AI opportunities. Engage with functional leads to clarify requirements, convert them into analytical hypotheses, rapidly prototype and iterate solutions.
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Lead AI Project Lifecycle: Own the end-to-end process from ideation and stakeholder engagement to deployment and post-launch evaluation of AI and LLM initiatives.
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Model Development & Deployment: Execute the full data-science workflow-including EDA, feature engineering, model selection, validation, and monitoring-adhering to team coding and documentation standards.
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LLM Application Development: Design and implement LLM powered applications, tailored to solve real estate-specific challenges (e.g., lease abstraction, tenant communication, investment memo summarization). Craft prompts, fine-tune domain-specific models, or create retrieval-augmented generation pipelines that boost productivity or customer experience.
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Deployment & Monitoring: Work with MLOps and engineering teams to deploy models into production environments, establish monitoring frameworks, and continuously improve solution performance.
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Cross-Functional Collaboration: Act as a bridge between product, engineering, data, and business teams to align AI solutions with user needs and technical feasibility.
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Insight Communication: Distill findings into clear narratives and visualizations; present recommendations to technical and non-technical stakeholders.
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Technical Guidance: Provide peer mentorship, code and architecture reviews, and technical best practices to elevate the broader team's capabilities
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Continuous Improvement: Stay current on emerging algorithms and tooling; propose POCs that can raise model accuracy, reduce latency, or lower cost.
Building blocks for success
Preferred
- 3+ years of hands-on experience in applied AI/ML development (1-2 years with advanced STEM degree), with at least 2 years focusing on LLMs or NLP-related technologies.
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Demonstrated ability to convert business questions into deployable ML solutions and explain results to non-experts.
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Proven success owning and delivering cross-functional AI/LLM projects from start to finish.
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Experience working in or supporting real estate, logistics, finance, or other asset-heavy industries is a plus.
Technical Skills
- Proficient in Python (pandas, scikit-learn, PyTorch/TensorFlow, Langchain etc), SQL, and version control.
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Solid grounding in supervised, unsupervised, and deep learning techniques plus model-evaluation best practices.
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Hands-on experience fine-tuning or integrating LLMs such as GPT, LLaMA, Claude, Gemini, etc.
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Experience with vector databases (e.g., FAISS, Pinecone), embeddings, and RAG architectures.
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Solid understanding of cloud platforms (AWS, Azure, GCP) and MLOps tools.
Hiring Salary Range of: $135,000 - $190,000. Salary and whole compensation package (bonus target) to be determined by the candidate's location, education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.
