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.