AI/ML & Data Engineering Specialist

ROLE SUMMARY

We are seeking an experienced AI/ML & Data Engineering Specialist (5–8 years) to design, build, and deploy end-to-end machine learning pipelines across MedTech, Pharmaceutical, and smart manufacturing environments.

This role combines:

• Machine Learning (supervised + unsupervised)
• Time-series modelling & Deep Learning
• Data Engineering (ETL/ELT & feature engineering)
• MLOps (CI/CD, containerization, deployment)
• Blueprint/Framework creation for scalable ML implementation

You will collaborate closely with onsite Business Systems Analysts (BSAs) and domain experts to understand workflows, interpret operational behaviour, and convert them into scalable ML and data workflows.

This role requires strong analytical capability, high independence, and comfort working in environments where datasets may be partially structured or evolving.

REQUIRED SKILLS & EXPERIENCE (5–8 YEARS)

Technical Skills

• Strong Python skills (Pandas, NumPy, SciPy, Scikit-learn)
• Experience with Deep Learning (TensorFlow / PyTorch)
• Expertise in time-series modelling and feature engineering
• ETL/ELT pipeline development and data transformation
• Containerization (Docker), Git, CI/CD pipelines
• Cloud familiarity (Azure/AWS) and hybrid deployments
• API development (FastAPI preferred)

Professional Skills

• Ability to work independently and handle ambiguous or evolving datasets
• Strong analytical and structured problem-solving skills
• Excellent communication skills for cross-functional collaboration
• Comfortable working in regulated environments with strong documentation expectations

PREFERRED EXPERIENCE

• Experience in MedTech, Pharma, or regulated manufacturing
• Exposure to ISO 13485, GxP, CSV, or validation-aligned documentation
• Familiarity with MES, QMS, Historian, or industrial data sources
• Background in predictive maintenance or operational intelligence solutions

QUALIFICATIONS

Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related fields

Certifications in ML Engineering, MLOps, Cloud, or Industry 4.0 are beneficial