years of experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact. Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow. Ability to write readable and maintainable code. Strong communication and storytelling skills with both technical and non-technical audiences. Ability to More ❯
cases. Proficient in one of the deep learning stacks such as PyTorch or Tensorflow. Working knowledge of parallelisation and async paradigms in Python, Spark, Dask, Apache Ray. An awareness and interest in economic, financial and general business concepts and terminology. Excellent written and verbal command of English. Strong problem-solving More ❯
of Python, R, and Java. Experience scaling machine learning on data and compute grids. Proficiency with Kubernetes, Docker, Linux, and cloud computing. Experience with Dask, Airflow, and MLflow. MLOps, CI, Git, and Agile processes. Why you do not want to miss this career opportunity? We are a mission-driven firm More ❯
ML models into production environments, including both batch and real-time/streaming contexts Proficiency working with distributed computing frameworks such as Apache Spark , Dask, or similar Experience with cloud-native ML deployment , particularly on AWS , using services like ECS, EKS, Fargate, Lambda, S3, and more Familiarity with orchestration and More ❯
/CD, and modern development workflows Solid understanding of data structures, algorithms, and performance tuning Nice-to-Have: Experience with distributed computing frameworks (e.g. Dask, Spark) Exposure to cloud platforms (AWS, GCP, Azure) Familiarity with SQL and relational databases Experience working in agile environments More ❯
