Sr Advanced AI Engineer

Senior Advanced AI Engineer

As a Senior Advanced AI Engineer, you will design, develop, and deploy AI-driven solutions for smart buildings and industrial automation systems. Your primary focus will be building advanced ML models, integrating them into real-world control environments, and driving innovation across HVAC, lighting, security, and energy optimization. You will collaborate cross-functionally, mentor junior engineers, and influence multiple projects with your technical expertise.

AI Solutions Design & Integration

• Design and integrate AI/ML models into Building Management Systems (BMS) and Industrial Control Systems (ICS), including SCADA and PLC environments.
• Implement real-time API–based and batch-inference workflows.
• Develop model feedback loops to support continuous learning and performance improvement.
• Build algorithms for real-time decision-making using sensor, IoT, and industrial process data.

Data Engineering

• Partner with Data Engineering teams on ETL workflows and data preparation for large-scale building and industrial datasets (e.g., HVAC telemetry, energy consumption, machine performance).
• Contribute to feature engineering and ensure data readiness for modeling.
• Support the development of training pipelines that leverage model registries and tracking systems.

Innovation & Research

• Explore emerging technologies such as generative AI, digital twins, multimodal foundation models, and autonomous control systems.
• Lead proof-of-concept initiatives and mentor junior engineers through early-stage experimentation.
• Translate innovative concepts into practical solutions for automation and building intelligence.

Performance Optimization

• Collaborate with MLOps teams to optimize real-time inference across platforms (AKS, GKE, on-prem microk8s).
• Work with production-ready inference runtimes such as vLLM, ONNX Runtime, and NVIDIA Triton.
• Contribute to model conversion, quantization, and optimization for efficient inference.
• Partner with platform engineers on deployment strategies, scalability, and monitoring.

Compliance & Security

• Ensure all AI solutions comply with cybersecurity standards and industrial safety protocols.
• Maintain training and inference repositories to meet corporate and industry security requirements.

MUST HAVE

• Technical Expertise
• Strong proficiency in Python and ML libraries such as PyTorch, Tensor Flow, JAX, XGBoost, and scikit-learn.
• Experience with Kubernetes, Databricks, or comparable platforms.
• Familiarity with CI/CD practices for AI/ML workflows.
• Working knowledge of PySpark for data exploration and pipeline contributions.
• Strong debugging, profiling, and performance engineering skills in Python.
• AI/ML Knowledge
• Expertise in one or more key domains: NLP, time-series forecasting, computer vision, or reinforcement learning.
• Ability to build models with noisy or sparsely labeled datasets.
• Experience using MLflow or similar tools for tracking, reproducibility, and model registry.
• Knowledge of converting models for production inference (Torch Script, ONNX).
• Experience with model performance optimization (e.g., quantization, latency tuning).
• Working knowledge of applying, fine-tuning, and optimizing foundation models for domain-specific tasks across text, vision, or time-series modalities.
• Ability to make informed accuracy–cost trade-offs during model design.
• Innovation Skills
• Ability to identify emerging AI trends and translate them into practical solutions.
• Experience in rapid prototyping, proof-of-concept development, and technology scouting.
• Strong problem-solving mindset with a focus on creative and disruptive solutions.
• Cloud & Edge Computing
• Knowledge of AI/ML offerings from major cloud providers (Azure, GCP, or AWS).
• Experience deploying AI/ML solutions on edge devices (e.g., NVIDIA Jetson) is a plus but not mandatory.
• Education & Experience
• Bachelor's degree in Computer Science, Electrical Engineering, or a related field;
  Master's degree preferred.
• Bachelor's + 6 years of relevant AI/ML experience
• Master's + 4 years of relevant AI/ML experience
• PhD + 2 years of relevant AI/ML experience

WE VALUE

• Experience optimizing deep learning models for NVIDIA Jetson–based edge systems.
• Expe…