Careers

Senior Artificial Intelligence & Machine Learning Engineer

5+ years (or equivalent demonstrated expertise)

Job Summary

We are seeking a highly experienced Senior AI/ML Engineer with strong expertise in Artificial Intelligence, Machine Learning, and Deep Learning. The ideal candidate will have hands-on experience designing, training, fine-tuning, and deploying advanced ML models, particularly in computer vision, spatial intelligence, and geospatial applications. Exposure to AEC (Architecture, Engineering & Construction) and Geospatial Intelligence platforms / workflows is highly desirable.

Key Responsibilities

  • Design, develop, and deploy AI/ML and Deep Learning models for real-world applications
  • Lead research and implementation of state-of-the-art computer vision and image understanding models
  • Work with vector databases and similarity search systems such as FAISS
  • Evaluate and integrate emerging AI models and frameworks relevant to vision, spatial intelligence, and generative AI
  • Fine-tune and optimize statistical, classical ML, and deep learning models for performance and scalability
  • Collaborate with cross-functional teams including geospatial analysts, software engineers, and domain experts
  • Provide technical leadership, mentorship, and architectural guidance to junior ML engineers
  • Translate complex business or domain problems into robust AI-driven solutions

Required Technical Skills

Artificial Intelligence & Machine Learning:

  • Strong fundamentals in Artificial Intelligence, Machine Learning, and Deep Learning
  • In-depth knowledge of supervised, unsupervised, and semi-supervised learning
  • Hands-on experience with model training, fine-tuning, validation, and deployment

Statistical & Classical Machine Learning

Artificial Intelligence & Machine Learning

  • Strong fundamentals in Artificial Intelligence, Machine Learning, and Deep Learning
  • In-depth knowledge of supervised, unsupervised, and semi-supervised learning
  • Hands-on experience with model training, fine-tuning, validation, and deployment

Statistical & Classical Machine Learning

  • Proficiency in:
    • Random Forest
    • Support Vector Machines (SVM)
    • K-Nearest Neighbors (KNN)
    • XGBoost and other gradient boosting techniques
    • Ensemble learning methods
    • Bayesian optimization and statistical modeling concepts

Deep Learning & Neural Networks

  • Strong experience with:
    • Convolutional Neural Networks (CNNs)
    • Long Short-Term Memory (LSTM) networks
  • Familiarity with deep learning frameworks such as PyTorch and/or TensorFlow

Computer Vision & Image Intelligence

  • Strong understanding of advances in image processing, computer vision, and vision-based ML
  • Awareness and practical understanding of modern vision and foundation models including:
    • SpatialLM
    • MasterSLAM
    • DINO / DINOv2
    • Segment Anything Model (SAM)
    • IP-Adapter
    • Stable Diffusion and generative vision models
  • Ability to assess model capabilities, limitations, and applicability to real-world problems

Databases & AI Infrastructure

  • Experience with AI/ML databases and vector search systems, especially FAISS
  • Understanding of embedding-based retrieval, similarity search, and indexing strategies

Domain & Industry Exposure (Preferred)

  • AEC (Architecture, Engineering & Construction) workflows and data
  • Geospatial Intelligence & Spatial Analytics
  • Remote sensing, drone imagery, LiDAR, GIS, or 3D spatial data (desirable)

Soft Skills & Leadership

  • Strong analytical and problem-solving abilities
  • Excellent communication skills to explain complex AI concepts to technical and non-technical stakeholders
  • Ability to lead technical initiatives and mentor team members
  • Research-oriented mindset with awareness of emerging AI trends

Education

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, Data Science, Robotics, or a related field
  • Equivalent industry experience with demonstrable impact will also be considered