Posted:3 days ago| Platform: Linkedin logo

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About the Role
We are seeking a highly experienced and strategic AI/ML Architect to lead the design, development, and deployment of scalable artificial intelligence and machine learning solutions. As a core member of our technical leadership team, you will play a pivotal role in building intelligent systems that drive innovation and transform digital healthcare delivery across our AI Driven Telemedicine platform.Key ResponsibilitiesArchitect AI/ML systems that support key business goals, from real-time diagnosis and predictive analytics to natural language conversations and recommendation engines.Design and oversee machine learning pipelines, model training, validation, deployment, and performance monitoring.Guide selection of ML frameworks (e.g., TensorFlow, PyTorch) and ensure proper MLOps practices (CI/CD, model versioning, reproducibility, drift detection).Collaborate with cross-functional teams (data engineers, product managers, UI/UX, backend developers) to integrate AI into real-time applications and APIs.Build and maintain scalable AI infrastructure, including data ingestion, storage, and processing layers in cloud environments (AWS, GCP, or Azure).Lead research and experimentation on generative AI, NLP, computer vision, and deep learning techniques relevant to healthcare use cases.Define data strategies, governance, and model explainability/ethics frameworks to ensure compliance with regulatory standards like HIPAA.Mentor and lead a growing team of ML engineers and data scientists.QualificationsMust-Have:Bachelor's or Master’s degree in Computer Science, AI, Data Science, or related field (PhD preferred).7+ years of experience in AI/ML development, with at least 2 years in a lead or architect role.Proven experience designing and deploying production-grade ML systems at scale.Strong grasp of ML algorithms, deep learning, NLP, computer vision, and generative AI.Expertise in Python, ML libraries (TensorFlow, PyTorch, Scikit-learn), and ML Ops tools (MLflow, Kubeflow, SageMaker, etc.).Familiarity with data engineering pipelines (Airflow, Spark, Kafka) and cloud platforms.Strong communication and collaboration skills.Preferred:Experience with healthcare data standards (FHIR, HL7) and medical ontologies (SNOMED CT, ICD).Familiarity with AI ethics, fairness, and interpretability frameworks.Startup or early-stage product development experience.

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