• Develop and evaluate scalable deep learning algorithms that are central to our brain decoding initiatives. • Collaborate closely with data scientists to pioneer research in generative modeling and representation learning. • Identify bottlenecks in data processing pipelines and devise effective solutions, improving performance and reliability. • Maintain high standards of code quality, organization, and automatization across all projects. • Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs. • Write and revise papers, communicate and disseminate results.

• Develop and optimize ML models, ensuring scalability, monitoring, and integration with MLOps best practices. • Implement client requirements, from exploratory data analysis (EDA) to feature engineering and model lifecycle management. • Build ML Proof of Concepts (POCs) to validate and refine solutions. • Optimize models for performance, latency, memory, and throughput. • Apply statistical analysis techniques and develop regression models. • Design and maintain feature stores and data pipelines for ML workflows. • Research and implement emerging ML/AI techniques to enhance solutions. • Collaborate with stakeholders to align technical solutions with business needs.

• Lead and mentor the team, fostering skill development and best practices. • Guide the creation of SPECs and ensure clear documentation. • Act as the main point of contact for stakeholders, ensuring alignment between technical and business goals. • Develop and optimize data and ML solutions, integrating best practices for scalability and monitoring. • Oversee the full lifecycle of data pipelines and models—from EDA and feature engineering to deployment and continuous improvement. • Build Proof of Concepts (POCs) to validate and refine solutions. • Optimize performance, latency, memory, and throughput across data systems. • Design and maintain feature stores and data pipelines to support workflows. • Research and implement emerging technologies to enhance solutions. • Participate in candidate interviews and evaluations to help Mutt grow.

• Develop and deploy machine learning models, algorithms, and solutions to solve complex business problems. • Collect, preprocess, and analyze data to derive valuable insights and patterns for model training and optimization. • Collaborate with cross-functional teams to understand business requirements and translate them into machine-learning solutions. • Implement and optimize machine learning pipelines, ensuring scalability, reliability, and efficiency of the models. • Experiment with various machine learning algorithms, techniques, and frameworks to improve model performance and accuracy. • Stay updated on the latest trends in machine learning, AI technologies, and incorporating innovative approaches into our projects. • Conduct thorough model evaluation, testing, and validation to ensure the robustness and effectiveness of the solutions. • Document and communicate technical concepts, methodologies, and findings to stakeholders and team members.