<p>Join our team and become part of a company that thrives on innovation and continuous learning in the cloud and web development realms.</p><p>Responsibilities:</p><ul><li>Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with classic algorithms and machine learning models.</li><li>Alongside our Data Scientists, support machine learning-based solutions to our AI</li></ul><p>products from research to production.</p><ul><li>Lead complex projects from scratch while communicating with different stakeholders.</li><li>Build data monitoring tools for feature exploration and production model verification.</li><li>Adapt standard machine learning methods to exploit modern environments best.</li><li>Work closely with data scientists and domain experts on time series datasets.</li></ul>

<p>Requirements:</p><ul><li>BA in Computer Science or a similar degree, MSC advantage</li><li>Experience with developing and maintaining production machine learning pipelines</li><li>4+ years of hands-on experience in coding using Python</li><li>2+ years of experience as a Machine Learning Engineer</li><li>Independent, self-motivated, and auto-didactic with creative and critical thinking</li></ul><p>capabilities</p><ul><li>Experience in building machine learning models deployed to production environments</li><li>Familiarity with MLOPS tools like MLFlow, ArgoCD, SageMaker, and others - Advantage</li><li>Familiarity with monitoring tools - Advantage</li><li>Excellent problem-solving and critical thinking skills</li><li>Knowledge of software engineering best practices, version control, deployment</li><li>pipelines, testing, and object-oriented design (OOD).</li><li>Knowledge of Machine Learning tools and frameworks: sklearn, Numpy, Pandas, PyTorch, TensorFlow, Keras.</li><li>Familiarity with data tools such as DynamoDB, AWS-Athena, AWS-Glue, influxDB, etc</li><li>Experience with AWS – Advantage</li><li>Experience with CI/CD and agile methodologies</li></ul>