Back
Metro-based mid-level ML role, broad skill requirements, and common title create high applicant competition.
Requires specialized ML, MLOps, and data engineering expertise so candidates from unrelated fields fit poorly.
Explicit 5+ years plus mandatory ML frameworks, MLOps, cloud, and leadership requirements enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect, design, and deploy scalable AI/ML solutions on cloud platforms (AWS, GCP, Azure).
Lead model development in NLP, computer vision, generative AI, predictive analytics, including optimisation and feature engineering.
Oversee data pipelines, implement MLOps/LLMOps processes, and mentor junior engineers while collaborating cross-functionally.
5+ years of professional experience in AI/ML or a similar technical domain.
Proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
Experience with cloud-based ML deployment platforms (e.g., AWS SageMaker, VertexAI).
Expertise in advanced AI techniques (NLP with LLMs, transformers; computer vision; generative AI; RAG architectures) and MLOps tools (Docker, Kubernetes, CI/CD, MLflow, DVC).
Senior-level AI/ML professional comfortable leading end-to-end design and deployment of enterprise-grade AI systems.
Experienced in integrating complex AI models with cloud-native architectures and engineering scalable ML pipelines.
Able to lead teams technically and collaborate across product, engineering, and client functions to deliver impactful AI solutions.