Senior Artificial Intelligence & Machine Learning Engineer

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

• 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