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We seeking a talented ML/AI Engineer to join our innovative team and drive the development of cutting-edge machine learning solutions. This role offers the opportunity to work with state-of-the-art AI technologies while making a meaningful impact in our organization.
Job Responsibility:
Design, develop, and deploy robust machine learning models for various business applications
Build and optimize generative AI solutions using latest frameworks and techniques
Implement agentic AI systems that can autonomously perform complex tasks
Develop and maintain ML pipelines from data ingestion to model deployment
Leverage Google Cloud Platform (GCP) services for scalable ML infrastructure
Utilize Vertex AI for model training, deployment, and management
Implement AutoML solutions for rapid prototyping and model development
Ensure model security and compliance using Model Armour and related tools
Write clean, efficient Python code for ML applications and data processing
Optimize model performance, accuracy, and computational efficiency
Implement MLOps best practices for continuous integration and deployment
Collaborate with cross-functional teams to integrate ML solutions into existing systems
Stay current with latest developments in ML/AI, particularly in generative AI and agentic systems
Experiment with new technologies and frameworks to enhance capabilities
Contribute to technical documentation and knowledge sharing initiatives
Requirements:
Strong experience in building ML models with proven track record of successful deployments
Extensive experience in Generative AI including LLMs, diffusion models, and related technologies
Experience in Agentic AI and understanding of autonomous agent architectures
Proficiency with Model Control Protocol (MCP) for agent communication and control
Advanced Python programming with expertise in ML libraries (scikit-learn, TensorFlow, PyTorch, etc.)
Google Cloud Platform (GCP) experience with ML-focused services
Vertex AI hands-on experience for model lifecycle management
AutoML experience for automated machine learning workflows
Model Armour or similar model security and protection frameworks
3+ years of experience in machine learning engineering or related field
Demonstrated experience shipping ML models to production environments
Experience with MLOps practices and CI/CD pipelines for ML
Strong understanding of data engineering principles and practices
Excellent problem-solving abilities and analytical thinking
Strong communication skills for technical and non-technical stakeholders
Ability to work independently and manage multiple projects simultaneously
Collaborative mindset for cross-functional team environments
Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field
Nice to have:
Healthcare Industry Experience
Experience developing ML solutions for healthcare applications
Understanding of healthcare data standards (FHIR, HL7, DICOM)
Knowledge of healthcare compliance requirements (HIPAA, FDA regulations)
Experience with clinical decision support systems or medical imaging
Master's degree preferred but not required with equivalent experience
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