ML/AI Engineer

About Genzeon Delivering excellence in IT services and solutions for the retail and healthcare sectors. Genzeon is a leading provider of intelligent automation, security, compliance, cloud, and managed services. Our healthcare capabilities integrate data systems, facilitate information flow, and leverage interoperability to improve clinical and operational outcomes. Genzeon empowers retail enterprises with multichannel IT solutions that deliver a personalized experience for consumers. Genzeon is looking for talented ML/AI Engineers to be part of our innovative and fast-growing team. ML/AI Engineer C2H Remote (USA) Company Overview We are 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. Position Summary We are looking for an 8+ years experienced ML/AI Engineer with strong expertise in building machine learning models and generative AI solutions. The ideal candidate will have hands-on experience with agentic AI systems, cloud-based ML platforms, and modern AI frameworks. Healthcare industry experience is highly valued but not required. Key Responsibilities Model Development & Implementation • 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 Cloud & Platform Management • 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 Technical Excellence • 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 Innovation & Research • 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 Required Qualifications Technical Skills • 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 Professional Experience • 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 Soft Skills • 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 Preferred Qualifications Healthcare Industry Experience (Bonus) • 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 Education • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field • Master's degree preferred but not required with equivalent experience