AI/ML Engineer – Machine Learning & AI Solutions

About the role

The AI/ML Engineer will design, develop, and deploy machine‑learning models and AI‑driven solutions that support strategic business initiatives. Working closely with software engineers, data analysts, and business stakeholders, you will enable intelligent automation and data‑driven decision‑making across the organization.

Key responsibilities

• Design, build, and deploy ML models for classification, regression, NLP, computer vision, and time‑series forecasting.
• Prepare and transform structured and unstructured data, engineer features, and ensure data quality.
• Package models using Docker and serve them via Flask or FastAPI, orchestrating deployments with Kubernetes.
• Implement CI/CD pipelines for ML using tools such as MLflow, Airflow, or Kubeflow and monitor models for drift and performance.
• Collaborate with business units to translate problems into AI/ML use cases, prototype solutions like recommendation engines or fraud detection, and scale successful prototypes.
• Stay current with cutting‑edge research, experiment with LLMs, transformers, and generative AI, and propose innovative approaches.

Required profile

• 3–5 years of hands‑on experience developing and deploying machine‑learning models.
• Proven ability to solve real‑world problems using supervised, unsupervised, or deep‑learning techniques.
• Strong collaboration skills to work with cross‑functional teams and translate technical insights into business value.

Required skills

• Python programming.
• TensorFlow or PyTorch.
• Docker and Flask/FastAPI for model serving.
• Kubernetes for container orchestration.
• MLflow, Airflow or Kubeflow for CI/CD pipelines.