Senior AI Engineer – Healthcare Predictive Modeling

Note

Candidates whose primary experience is limited to integrating third-party LLMs, prompt engineering, or API-based AI solutions will not be considered.

This role requires hands-on healthcare AI modeling experience, not LLM consumption.

Job Summary

We are looking for a Senior AI / Machine Learning Engineer with direct experience in healthcare prediction and clinical data modeling. The role focuses on designing, building, training, and optimizing custom machine learning and deep learning models from scratch for healthcare use cases, such as patient risk prediction, clinical outcomes forecasting, utilization prediction, and anomaly detection in healthcare data.

This is not a role for candidates whose primary experience involves integrating third-party LLMs, writing prompts, or consuming AI APIs.

The ideal candidate has strong fundamentals in mathematics, statistics, and algorithms, and proven experience developing production-grade ML/DL models in Python using real healthcare datasets (EHR, claims, time-series, or clinical data).

What This Role IS

• Building custom ML/DL models for healthcare prediction problems
• Designing model architectures for clinical and healthcare datasets
• Training, tuning, and evaluating models for healthcare outcomes
• Working with raw healthcare data → features → models → deployment
• Research-driven and engineering-driven healthcare AI work

What This Role IS NOT

❌ Prompt engineering

❌ LLM API integration (OpenAI, Gemini, Claude, etc.)

❌ Glue code around pre-trained models

❌ No-code / low-code AI tools

Key Responsibilities

• Design and implement healthcare-focused ML/DL models from scratch (supervised, unsupervised, deep learning)
• Develop and train models using PyTorch / TensorFlow / JAX
• Perform feature engineering and preprocessing on healthcare data (EHR, claims, clinical, time-series)
• Build predictive models for:
• Patient risk stratification
• Clinical outcome prediction
• Readmission or utilization forecasting
• Anomaly detection in healthcare data
• Optimize models for accuracy, robustness, and scalability in healthcare settings
• Implement training pipelines, evaluation metrics, and validation strategies suitable for clinical data
• Handle class imbalance, missing data, bias, and drift common in healthcare datasets
• Deploy models into production and monitor real-world healthcare performance
• Collaborate with backend, data, and product teams on healthcare model integration

Required Skills (Must-Have)

• Strong Python (NumPy, Pandas, SciPy)
• Deep understanding of ML fundamentals:
• Linear algebra
• Probability & statistics
• Optimization techniques
• Hands-on experience building models using:
• PyTorch or TensorFlow
• Proven experience with healthcare prediction models, including:
• Regression, classification, clustering
• Time-series modeling on clinical data
• Architecture-level understanding of:
• CNNs, RNNs, Transformers
• Experience training models on real healthcare datasets (not just tutorials)
• Ability to explain why a healthcare model works, including assumptions and limitations

Nice to Have

• Experience building healthcare models such as:
• Patient risk scoring systems
• Clinical decision support models
• Readmission or length-of-stay prediction
• Anomaly or fraud detection in claims data
• Experience with:
• Distributed training
• Model compression / quantization
• MLOps (MLflow, Kubeflow, custom pipelines)
• Familiarity with healthcare data challenges (missing values, imbalance, bias)
• Research background or published work in healthcare AI / ML

Experience Level

• 5+ years of hands-on experience in machine learning / AI modeling
• Proven experience building and deploying healthcare-focused predictive models

Job Type: Full-time

Pay: Rs500,000.00 - Rs600,000.00 per month

Application Question(s):

• This role requires strong healthcare AI experience. Please apply only if you meet this requirement. Do you have at least 5 years of ML/AI experience with direct healthcare prediction or clinical data?
• Give a brief about the healthcare predictive project that you have experience of?
• Are you willing to work onsite from 12:00 PM to 9:00 PM at our Evacuee Trust Complex (F-5), Islamabad?
• your joining time if selected (In Days)

Work Location: In person