Senior Machine Learning Engineer

**Company Description** deepsense.ai is an AI partner that helps organizations design, build, and scale production\-grade AI systems that deliver measurable ROI in a reliable and secure way. The company works end\-to\-end with clients, from initial concept through deployment and maintenance of AI solutions. deepsense.ai collaborates with leading technology providers such as OpenAI, Anthropic, Google Cloud, and AWS to access cutting\-edge tools and platforms. The organization also develops proprietary solutions, including the GenAI accelerator ragbits, to enhance the performance and impact of generative AI applications. Team members join a environment focused on practical innovation and long\-term value for clients. **Role Description** This is a full\-time, on\-site Senior Machine Learning Engineer role based in Warsaw. The person in this role will design, train, and optimize machine learning and deep learning models for production\-grade AI systems, with a focus on reliability, scalability, and measurable business impact. Daily responsibilities include developing and evaluating algorithms, implementing neural network architectures, performing data preprocessing and feature engineering, and conducting experiments to improve model performance. The Senior Machine Learning Engineer will collaborate closely with data scientists, software engineers, and product teams to integrate models into production environments, monitor performance, and address technical challenges. The role also involves code review, documentation, mentoring less experienced team members, and contributing to architectural and technical decisions across projects. **Qualifications** * Strong foundation in Computer Science and Algorithms, with experience designing efficient, scalable solutions. * Expertise in Pattern Recognition and Neural Networks, including practical experience building and deploying deep learning models. * Solid understanding of Statistics and applied mathematical methods used in machine learning and data analysis. * Proficiency in programming languages commonly used in ML (e.g., Python) and frameworks such as TensorFlow, PyTorch, or similar. * Experience taking ML models from prototype to production, including CI/CD practices, testing, and monitoring in cloud or on\-prem environments. * Ability to work collaboratively in cross\-functional teams, communicate technical concepts clearly, and mentor other engineers. * Bachelor’s or Master’s degree in Computer Science, Mathematics, Engineering, or a related technical field, or equivalent practical experience. * Experience with cloud platforms (e.g., AWS, Google Cloud) and interest in generative AI and large\-scale ML systems is highly beneficial.