Senior AI/ML Engineer
7 days ago
About Us Beatly.AI is a fast-growing artificial intelligence company focused on building intelligent, data-driven solutions that make a real-world impact. We develop cutting-edge technologies that enhance decision-making and efficiency across critical domains. If you're passionate about creating meaningful AI products and thrive in a collaborative, innovation-driven environment, we’d love to have you on our team. About the Role We are looking for a Senior AI/ML Engineer with strong hands-on experience in Convolutional Neural Networks (CNNs) and traditional deep learning techniques. The role involves designing, developing, and deploying machine learning models for pattern recognition and time-series or image-based applications. You’ll work closely with data engineers, software developers, and domain experts to build reliable and scalable AI systems from research prototypes to production-ready solutions. Key Responsibilities • Design and implement deep learning models (CNN, RNN, LSTM) for data classification, segmentation, or prediction tasks. • Develop robust data preprocessing and feature extraction pipelines for structured and unstructured datasets. • Optimize model architecture, training, and inference for performance and scalability. • Analyze and interpret model outputs, ensuring reliability and explainability. • Collaborate with cross-functional teams to integrate AI models into production environments. • Conduct model evaluation using statistical and domain-relevant performance metrics. • Mentor junior engineers and contribute to design discussions and technical reviews. Required Skills & Experience • 4–10 years of experience in applied machine learning or deep learning development. • Proven expertise in CNN-based model design for image or signal data. • Proficiency in Python and major deep learning frameworks such as TensorFlow , PyTorch , or Keras . • Strong understanding of signal processing , data normalization, and augmentation techniques. • Familiarity with model optimization , quantization, and deployment practices. • Experience with version control (Git) and ML Ops tools (Docker, Kubernetes, or cloud ML platforms). • Solid grounding in mathematics, statistics, and algorithm design . Preferred Qualifications • Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field. • Experience with time-series data analysis or real-time inference systems . • Background in end-to-end AI pipeline development — from data collection to deployment. • Exposure to regulatory or safety-critical environments is a plus. What We Offer • Opportunity to build and deploy cutting-edge AI systems with real-world impact. • Collaborative and technically strong R&D environment. • Competitive compensation, flexibility, and professional development opportunities. • Access to diverse datasets and advanced computing infrastructure.
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