Mohammed Ishaq Khan

About Mohammed Ishaq Khan

Senior MLOps Engineer with 7+ years of experience designing, deploying, and maintaining scalable AI/ML solutions across healthcare, finance, logistics, and energy industries. Proven ability to develop and operationalize intelligent systems that streamline processes, reduce costs, and drive measurable business outcomes.Currently at RxSense, leading the design and deployment of cloud-native ML infrastructures that deliver secure, automated, and high-performance AI applications. Previously served as an ML Engineer/Data Scientist at Total Bank Solutions, optimizing predictive modeling and ML pipelines for financial analytics, and as a Data Analyst at Optum Global Solutions, delivering insights that improved healthcare outcomes and efficiency.Skilled in Generative AI, NLP, Cognitive Search, and Deep Learning using TensorFlow, PyTorch, Keras, and Scikit-Learn. Proficient in Python, PySpark, Databricks, Apache NiFi, Apache Beam, and Dataflow for scalable data engineering and automation. Strong command of SQL Server, Oracle, BigQuery, and RDBMS for optimized data management.Hands-on expertise with AWS, Azure, and GCP, including Vertex AI, Azure ML, AWS Lambda, S3, and Redshift, enabling distributed training, cost optimization, and analytics. Experienced with Kubernetes, Docker, Jenkins, GitLab, and Azure DevOps for CI/CD automation and lifecycle management, with monitoring via Grafana and Prometheus.Delivered serverless ML deployments and edge AI applications, reducing infrastructure costs by 40% and latency by 60%. Ensured GDPR, CCPA, and HIPAA compliance through strong data governance and security. Collaborative leader skilled in Agile practices, mentoring teams, and integrating Salesforce, ServiceNow, and Workday via secure APIs.Authorized to work in the U.S. under U Visa EAD (W2/FTE) and actively seeking new opportunities in MLOps, ML Engineering, or Data Science to drive innovation and scalable AI transformation.

Experience

1. Sr Agentic Ai Engineer Sr Data Scientist

   RxSense

   Jun 2024 — Present · Boston, MA, US

   Major Duties & Key Responsibilities:• Designed and deployed agentic AI pipelines using Azure OpenAI and Azure Functions to automatically detect, triage, and resolve anomalies in claims and billing workflows, minimizing manual intervention and improving operational accuracy.• Built intelligent AI agents integrated with Azure Logic Apps and REST APIs to orchestrate cross-platform automation between CRM, EDI, and eligibility systems, improving workflow consistency and scalability.• Developed goal-oriented NLP models leveraging Bio BERT, Clinical BERT, and LSTM architectures to extract PHI/PII, diagnosis codes, and procedure details from unstructured clinical notes and HL7 messages, enabling automated data validation.• Engineered and deployed AI/ML models in Azure Machine Learning Studio to predict patient readmission risk, optimize claims adjudication, and identify high-risk members within chronic care programs.• Automated real-time eligibility and diagnosis verification by integrating intelligent agents with EDI and CRM systems, reducing claim approval turnaround by over 40%.• Designed end-to-end ETL and ML pipelines using Azure Data Factory and Azure Databricks to ingest, cleanse, and transform high-volume healthcare data from EDI X12, HL7, and internal claim systems into curated datasets for training and analytics.• Utilized Azure Data Lake Gen2 for managing raw, cleansed, and transformed data zones, enabling structured data governance and compliance with healthcare standards.• Containerized AI models using Docker and deployed scalable workloads via Azure Kubernetes Service (AKS) and Azure Container Instances (ACI), exposing RESTful endpoints through Azure API Management for real-time consumption.

Education

• University of the Cumberland’s

  Master, Data Science

• University of the Cumberlands

  Master's degree, Data Science

• Osmania University, Hyderabad

  Bachelor of Commerce - BCom, Computer Science

• Osmania University

  Bachelor, Commerce (Computers)