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Saltmine

AI/ML Engineer

Bengaluru, Karnataka, India

What you’ll work on

Full posting
  • You will work at the intersection of: ● computational geometry ● optimization algorithms ● real-world workplace design

From the employer’s posting
Saltmine is building an AI-powered workplace strategy and capital projects platform for enterprise real estate teams. We help global organizations move from business goals → spatial programs → stack plans → test fits → execution in a seamless, data-driven workflow. Our platform combines: ● Workplace strategy ● Occupancy planning ● Capital project planning ● AI-driven automation to enable faster, smarter, and more cost-efficient real estate decisions. We are now building a next-generation automated test-fitting engine that can generate high-quality, architecturally valid layouts in minutes and we’re looking for a Spatial Algorithms Engineer to help power this core capability. Role Overview As a Spatial Algorithms Engineer, you will design and build the core layout engine that generates optimized floor plans based on spatial constraints, architectural rules, and business requirements. You will work at the intersection of: ● computational geometry ● optimization algorithms ● real-world workplace design Your work will directly power Saltmine’s ability to automatically generate and evaluate thousands of layout options for enterprise customers.

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Tools in this posting

  • python
  • rust
  • c++
Source — Tool mentions in context
Note: We are open for any other technique, the idea is to work towards a solution which is best in industry. Programming ● Strong in: ○ Python (preferred) ○ or C++ / Rust for performance-critical systems Data Structures for Spatial Systems ● Grids, graphs, spatial indexing ● Quadtrees / BSP trees (good to have)

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Bengaluru, Karnataka, India

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Sep 9, 2026
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Job description

About Saltmine

Saltmine is building an AI-powered workplace strategy and capital projects platform for
enterprise real estate teams. We help global organizations move from business goals →
spatial programs → stack plans → test fits → execution in a seamless, data-driven
workflow.
Our platform combines:
● Workplace strategy
● Occupancy planning
● Capital project planning
● AI-driven automation
to enable faster, smarter, and more cost-efficient real estate decisions.
We are now building a next-generation automated test-fitting engine that can generate
high-quality, architecturally valid layouts in minutes and we’re looking for a Spatial Algorithms
Engineer to help power this core capability.

Role Overview
As a Spatial Algorithms Engineer, you will design and build the core layout engine that
generates optimized floor plans based on spatial constraints, architectural rules, and business
requirements.
You will work at the intersection of:
● computational geometry
● optimization algorithms
● real-world workplace design

Your work will directly power Saltmine’s ability to automatically generate and evaluate
thousands of layout options for enterprise customers.

Key Responsibilities

1. Build Automated Test-Fit Engine
● Develop algorithms to generate 2D layouts within complex floor plates
● Solve for:
○ space allocation
○ corridor generation
○ adjacency constraints
○ geometric validity

2. Design Constraint-Based Systems
● Encode real-world rules into the system:
○ door placement
○ circulation access
○ daylight constraints
○ minimum room geometry
● Implement hard and soft constraint frameworks

3. Optimization & Layout Generation Systems
● Build multi-objective optimization systems to balance:
○ adjacency satisfaction
○ space efficiency
○ daylight utilization
○ constraint compliance
● Apply techniques like:
○ greedy algorithms
○ simulated annealing
○ genetic algorithms
○ constraint solvers

4. Geometry & Spatial Modeling Systems
● Work with:
○ polygons and floor plate boundaries
○ spatial partitioning
○ graph-based circulation systems
● Implement:
○ space subdivision

○ packing algorithms
○ layout refinement logic

5. Scoring & Evaluation Systems
● Design scoring engines to evaluate layout quality:
○ adjacency score
○ circulation efficiency
○ residual space
○ program compliance

6. Performance Optimization
● Ensure system can:
○ generate multiple layouts efficiently
○ scale to large enterprise floor plates
○ support near real-time feedback

7. Cross-Functional Collaboration
● Work closely with:
○ product managers
○ architects / workplace strategists
○ frontend / visualization teams

Required Skills

Core Computer Science & Algorithms
● Strong foundation in:
○ data structures
○ algorithms
○ graph theory

Computational Geometry
● Hands-on experience with:
○ polygon operations (intersection, clipping, partitioning)
○ spatial reasoning and layout systems
● Familiarity with libraries like:
○ Shapely / GEOS
○ JTS / Turf.js
○ CGAL

Optimization Techniques
● Experience with:
○ constraint solving
○ heuristic optimization
● Exposure to:
○ simulated annealing
○ genetic algorithms
○ linear/integer programming

Note: We are open for any other technique, the idea is to work towards a solution which is best
in industry.

Programming
● Strong in:
○ Python (preferred)
○ or C++ / Rust for performance-critical systems

Data Structures for Spatial Systems
● Grids, graphs, spatial indexing
● Quadtrees / BSP trees (good to have)

Good to Have
● Exposure to AEC / architecture / workplace planning
● Experience with:
○ CAD / BIM tools (AutoCAD, Revit)
○ Rhino / Grasshopper
● Background in:
○ game development (procedural generation)
○ robotics (path planning)
○ simulation systems

What We’re Looking For
● Strong problem-solving mindset with ability to translate real-world constraints into
algorithms

● Comfort working with geometry, layouts, and visual systems
● Ability to balance multiple competing constraints in optimization problems
● Ownership mindset and ability to build 0 → 1 systems

Impact
● Build the core engine powering automated workplace planning
● Directly influence how global enterprises design offices
● Work on a category-defining product in PropTech + AI

Interview Process
● Algorithm & case study round - A real problem statement
● Discussion around case study
● Technical discussion
● Final discussion with leadership