Solution Architect

• 6+ years of proven experience as a Solutions Architect, ML Engineer, or similar role delivering AI/ML projects at scale.
• Solid understanding of AI/ML concepts: supervised and unsupervised learning, LLMs, NLP, computer vision, and model lifecycle management.
• Excellent communication and presentation skills, able to interface effectively with technical and non-technical stakeholders.
• Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML, Amazon Bedrock and Azure AI Foundry).
• Experience designing data architectures (batch & streaming) and working with big data technologies.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
• Traveling: Must be available to travel as needed for meetings, conferences, and project requirements.
• Languages: proficient in English

Preferred Qualifications

• Experience with AI model optimization, quantization, or deployment to edge.

• Knowledge of data privacy and ethical considerations in AI.

• Hands-on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face)

• Experience developing computer vision models, covering data collection, augmentation, training of deep learning models (e.g., CNNs, ViTs) for detection and segmentation tasks, and deploying optimized solutions to edge platforms (e.g. TensorRT, quantization)

• Direct experience with embedded systems, including low-level electronics programming for PLC, FPGAs or GPU architectures, combined with a working knowledge of AI model deployment and optimization.

• Familiarity with MLOps tools and practices: CI/CD, monitoring, orchestration frameworks (e.g., Kubeflow, Flyte, MLflow, Kubernetes, Docker)