Job Description
Experience Required:
8-10 years in IT, with a minimum of 8 years focused on AI/ML solutions architecture, development, and deployment.
Key Responsibilities:
- Architect and design robust, large-scale AI/ML solutions across multiple domains, including Generative AI.
- Lead and oversee the complete machine learning lifecycle, encompassing data ingestion, feature engineering, model development, deployment, and continuous monitoring.
- Partner with business and technical stakeholders to translate requirements into scalable and efficient ML systems.
- Establish and enforce best practices, standards, and governance frameworks for ML pipelines, MLOps, and data platform management.
- Provide mentorship and technical guidance to data scientists, ML engineers, and solution architects.
- Assess emerging AI/ML technologies and drive their adoption within enterprise environments.
- Ensure AI/ML solutions meet security, compliance, and performance benchmarks.
Required Skills & Qualifications:
- Deep expertise in Generative AI, Agentic AI, machine learning, deep learning, NLP, and big data ecosystems.
- Proficiency with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn; cloud AI platforms including AWS, Azure, and GCP; and MLOps tools like Kubeflow, MLflow, Airflow, Docker, and Kubernetes.
- Strong understanding of data architecture, API design, and scalable microservices.
- Hands-on programming experience in Python or equivalent languages.
- Proven experience delivering enterprise-scale AI/ML solutions.
- Excellent leadership abilities, with strong stakeholder management and communication skills.
