AI/ML Engineer

Company Description

NovintiX is a leading provider of innovative engineering services with a mission to empower transformative solutions across industries such as Medical Devices, Life Sciences & Healthcare, Aerospace & Defense, Automotive, Consumer Electronics, and Industrial & Heavy Equipment. Dedicated to excellence, we deliver products and services that align with technological advancements and future-forward strategies. Specializing in areas like Product Engineering, Supply Chain & Manufacturing, Quality, Clinical Affairs, and Digital Solutions, our focus remains on meeting the evolving needs of our clients. At NovintiX, we emphasize fostering growth, learning, and innovation for both our customers and employees

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About the Role

We are seeking a highly skilled and experienced AI/ML Engineer to design, build, and deploy data-driven solutions in the healthcare and MedTech domain. The ideal candidate will have expertise in developing and deploying machine learning models, working with large-scale data systems, and implementing AI innovations to solve complex clinical and operational challenges.

Key Responsibilities

Machine Learning Development

Design, develop, train, and deploy ML/DL models for clinical and operational usecases.

Develop predictive analytics solutions (e.g., patient risk scoring, diagnostics, readmission n prediction).

Fine-tune algorithms using frameworks such as scikit-learn, TensorFlow, and PyTorch

Apply LLMs, Generative AI, or RAG methods for medical text analysis and documentation automation.

Work with time series data for forecasting, anomaly detection, and trend analysis.

Data Engineering & Processing

Collaborate with data engineers to build scalable data pipelines using Databricks, Azure Data Factory, and SQL Server

Process structured and unstructured healthcare datasets; ensure data quality and feature engineering.

Leverage PySpark, Spark SQL, and SQL for large-scale data processing.

Model Deployment & MLOps

Deploy models into production using MLflow, Azure ML, or Kubeflow

Monitor and retrain models to maintain performance, reliability, and compliance.

Integrate models into BI tools or clinical applications for real-timeinsights.

Visualization & Reporting

Build dashboards in Power BI, Tableau, or QlikSense to visualize

ML outputs.

Communicate insights and model results effectively to technical and non-technical stakeholders.

Collaboration & Research

Work cross-functionally with clinicians, analysts, and engineers to define ML problems.

Guide and mentor junior team members.

Research emerging AI/ML methodologies and apply innovations to healthcare data.

Qualifications & Skills

Minimum 5+ years in AI/ML Engineering or Data Science, preferably in Healthcare, MedTech, or Manufacturing.

Programming: Python, SQL, PySpark, Spark SQL

Frameworks: scikit-learn, TensorFlow, PyTorch, Keras

Data Tools: Databricks, Azure Data Factory, Apache Spark

Cloud: Azure (preferred), AWS, GCP

BI Tools: Power BI, Tableau, QlikSense

MLOps: MLflow, Azure ML, Docker, Git, CI/CD

Healthcare Data Standards: HL7, FHIR (advantageous)