. This role is ideal for a technically versatile professional who thrives at the intersection of intelligent systems, data engineering, and automation technologies. You'll be instrumental in designing, building, and deploying intelligent automation solutions to optimise business processes and unlock efficiency at scale.
Key Responsibilities:
Machine Learning & Intelligent Automation
Design and implement machine learning models to solve business problems in areas such as process automation, predictive maintenance, and anomaly detection.
Develop and deploy automation workflows using RPA tools (e.g., UiPath, Blue Prism, Power Automate).
Apply advanced analytics and ML techniques to optimise and automate repetitive and rule-based business processes.
Collaborate with cross-functional teams to identify automation opportunities and assess their feasibility.
Continuously monitor, refine, and retrain models in production environments.
Data Engineering & Infrastructure
Build and maintain robust, scalable data pipelines for training and deploying machine learning models.
Integrate data from various sources (structured and unstructured) to support automation use cases.
Collaborate with cloud engineers to ensure seamless model deployment in production (Azure, AWS, or GCP).
Ensure data quality, integrity, and compliance with governance standards.
RPA Development & Orchestration
Develop intelligent bots and automation solutions that integrate with business systems.
Work with stakeholders to design end-to-end workflows and ensure they meet operational and security standards.
Combine RPA with AI/ML capabilities to develop intelligent process automation (IPA).
Innovation & Continuous Improvement
Stay up to date with advancements in ML, automation, and AI, recommending emerging tools or techniques.
Contribute to the organisation's automation strategy by identifying high-impact use cases.
Provide thought leadership on the convergence of machine learning and robotics in enterprise environments.
Key Skills & Technologies:
Essential:
Strong experience with ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
Proficient in Python for both ML and data engineering tasks.
Hands-on experience with RPA tools (e.g.,
UiPath
,
Automation Anywhere
,
Blue Prism
, or
Microsoft Power Automate
).
Cloud computing experience (preferably Azure or AWS).
SQL and experience with building/maintaining
ETL pipelines
.
Experience in deploying ML models in production environments (CI/CD, Docker, APIs).
Preferred:
Exposure to computer vision, NLP, or reinforcement learning.
Familiarity with robotics software libraries (e.g., ROS) is a plus.
Experience with event-driven architecture or microservices.
Qualifications & Experience:
Essential:
Bachelor's or Master's in Computer Science, Engineering, Data Science, or related field.
3-6 years of experience in machine learning, with proven automation or RPA project delivery.
Demonstrated ability to integrate data science solutions into real-world business operations.
Preferred:
Certifications in ML (Azure, AWS ML Engineer), RPA tools, or cloud platforms.
Experience in process optimisation or digital transformation projects.
This is a high-impact role for someone who is passionate about
intelligent automation
, data, and cutting-edge technology. If you're excited to shape the future of automation with machine learning and robotics, this opportunity is for you.
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Skills
==========
Machine LearningRobotic Process Automation (RPA)Data Engineering
Industries
==============
Financial ServicesBanking
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