AI/ML Engineer

Job Description:

We are seeking a highly skilled AI/ML Engineer to join our team and play a key role in building and optimizing machine learning solutions for large-scale supply chain optimization, predictive analytics, and multi-modal data insights. The ideal candidate will have a strong background in machine learning, cloud-based AI solutions, and real-time data processing.

Key Responsibilities:

• Implement infrastructure systems for real-time model inference and monitoring in production environments.
• Support the design and development of scalable machine learning models for supply chain optimization and predictive analytics.
• Innovate with cutting-edge techniques in NLP, computer vision, and time-series modeling to extract actionable insights from diverse datasets.
• Build end-to-end pipelines to train, validate, and deploy ML models using modern frameworks and cloud services.
• Develop tools to evaluate and monitor model performance, fairness, and explainability across different applications.

Requirements:

• 5 years of experience in designing, building, and deploying ML models in production environments.
• Familiarity with MLOps practices, including MLflow, CI/CD pipelines for ML, model versioning, and automated retraining workflows.
• Proven experience with cloud-based ML workflows, particularly in AWS, Azure, or Google Cloud Platform.
• Strong foundation in machine learning algorithms, statistical methods, and optimization techniques.
• Experience with real-time data processing and streaming platforms such as Kafka
• Ability to work collaboratively in an Agile/Scrum environment, balancing innovation with rapid iteration.

AI Skills:

• Experience in Natural Language Processing (NLP), Computer Vision, and Generative AI models.
• Knowledge of transformer architectures such as BERT, GPT, and Vision Transformers (ViTs).
• Hands-on expertise in training and fine-tuning deep learning models using TensorFlow, PyTorch,
• Familiarity with AI model interpretability, fairness, and bias mitigation techniques.
• Experience in developing AI-powered automation and intelligent decision-making systems.

Preferred Qualifications:

• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Hands-on experience in deploying ML models in containerized environments (Docker, Kubernetes).
• Strong programming skills in Python, Java, or Scala.
• Experience with feature engineering and data pipeline development.