What We Look For:
10+ years of total experience in machine learning and software engineering.
Fluency in Python.
Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, and NLP.
Familiarity with popular ML libraries like scikit-learn, Keras, TensorFlow, PyTorch, numpy, and pandas.
Proven experience in building scalable backend systems focused on data processing and analytics.
Strong programming skills in Python, Java, or Scala.
Experience with cloud platforms like AWS, Azure, or Google Cloud Platform.
Familiarity with big data technologies such as Apache Spark, Hadoop, and Kafka.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Knowledge of MLOps practices and tools such as MLflow, Kubeflow, or TFX.
Good understanding of the machine learning project lifecycle.
Alignment with our core values: positivity, clear communication, curiosity, and a proactive approach to building solutions.