We are seeking a Machine Learning Engineer to design and deploy nextgeneration AI and machine learning solutions at scale. This role focuses on building productionready models, robust ML pipelines, and modern AI capabilities that translate business needs into realworld impact.

Key Responsibilities

Design, develop, and deploy machine learning models and AI systems into production
Build and maintain scalable ML pipelines covering data ingestion, training, evaluation, deployment, and monitoring
Collaborate with cross-functional teams to translate business requirements into AI/ML solutions
Optimise models and systems for performance, scalability, and reliability in production environments
Implement MLOps best practices including CI/CD, model versioning, experiment tracking, and automated retraining
Monitor and maintain model performance, including handling drift and system reliability
Develop and integrate AI capabilities across domains such as computer vision, natural language processing, and modern approaches including generative AI or agent-based systems where applicable
Ensure adherence to data governance, security, and best engineering practices

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field
3+ years of experience in machine learning engineering, AI engineering, or related roles
Strong programming and software engineering skills
Hands-on experience with machine learning and modern AI/agentic frameworks (e.g., PyTorch, scikit-learn, LangChain, or similar)
Understanding of the end-to-end machine learning lifecycle, including data preparation, model development, evaluation, deployment, and monitoring
Understanding of software engineering best practices (testing, version control, CI/CD)
Familiarity with a range of machine learning techniques across domains such as computer vision, natural language processing, and/or generative AI
Experience with data processing tools and large-scale data systems
Experience building and deploying machine learning models in production environments
Experience deploying applications using APIs, containers, and orchestration tools
Familiarity with cloud platforms (AWS, Azure, or GCP)

Machine Learning Engineer (AI/ML Lab)