- Recruitment Drive: Delhi
- Date: 23rd & 24th May
- Position: AI Specialist (AI Engineer/Design Researcher)
- Experience: 2 to 25 Years.
- Hiring for Pune & Bengaluru Location
About Company
You may visit Dar Al-Handasah and Sidaracollaborative.
Role Overview
The AI Engineer is the foundational technical hire for the Applied AI for Design team. This role is responsible for taking AI use cases from problem definition to production-grade tools used on live Dar projects. This person sets the engineering bar for everything the team builds — how we package, deploy, monitor, and iterate on AI systems in an architecture and engineering environment. They work alongside senior architects and BIM leads who supply the domain knowledge, focusing their own craft on the AI engineering itself.
Key Responsibilities
- Design and build end-to-end AI systems: data pipelines, model training or fine-tuning, evaluation, deployment, monitoring, and the application layer that exposes the model to users
- Establish the team's core engineering patterns — how AI tools are packaged, exposed (Revit/Rhino plugins, web apps, APIs), and operated in production
- Build vertical data slices that support specific tools, designed for reuse as the team's data layer matures
- Stand up MLOps and evaluation practices: model versioning, regression testing, performance monitoring, incident response
- Work directly with senior architects and BIM leads to understand workflows, observe pain points, and translate them into systems that get used
- Document architectural decisions, patterns, and trade-offs so the team scales without losing coherence
Requirements
- 2–25 years of applied ML / AI engineering experience, with at least two years shipping production systems used by real users
- Strong Python with production-quality engineering habits: testing, code review, version control, CI/CD
- Hands-on experience deploying at least one of: large language models with RAG, computer vision systems, or 3D/geometric ML systems
- Comfort across the full AI product stack — from data pipeline to deployed user-facing tool
- Demonstrated ability to ship iteratively, hardening over time rather than waiting for perfection
- Experience working directly with non-technical end users and translating their workflows into systems
- Bachelor's or Master's degree in Computer Science, Machine Learning, Software Engineering, or a related field (or equivalent industry experience)
Nice to Have
- Experience with agentic LLM systems, retrieval-augmented generation over technical documents, computer vision for inspection, or 3D/geometric deep learning
- Familiarity with cloud AI infrastructure (Azure, AWS, or GCP) and modern MLOps tooling
- Experience integrating AI into desktop applications, plugins, or vertical software environments
- Prior exposure to architecture, engineering, construction, or built-environment data (IFC, Revit API, CAD geometry, point clouds, simulation outputs)
- Background in computational design, parametric modeling, or generative design
- Open-source contributions, technical writing, or talks in the AI/ML community
Interview Process:
- Candidates whose profiles align with the required technical criteria will be shortlisted and invited by the recruitment team through email to participate in the Recruitment Drive.
- You can share your CV & Portfolio at following email addresses:
- [Confidential Information]
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