Machine Learning Engineer

This is a fully remote position, open to applicants in Argentina, +3 more countries.

📋 Description

• Oversee the design, development, and implementation of machine learning models.

• Manage extensive and intricate datasets to derive meaningful insights and establish predictive analytics pipelines.

• Partner with data engineers to design and enhance cloud-based data solutions.

• Convert business challenges into data-centric solutions utilizing statistical modeling and machine learning methods.

• Streamline data workflows and the deployment of models through the use of cloud services and CI/CD tools.

• Provide mentorship to junior data scientists and advocate for best practices in model development and operationalization.

• Present findings and strategic suggestions to stakeholders and executive management.

• Assist clients in constructing scalable architectures, resilient data engineering pipelines, data consumption layers, as well as ML and AI applications.

⛳️ Requirements

• A minimum of 4 years of experience in data science or machine learning roles.

• Expertise in Python, including libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.

• Proficient in SQL.

• Strong foundation in statistics, A/B testing, and machine learning algorithms.

• Experience in building and deploying models within production settings.

• Knowledge of MLOps practices and tools, such as MLflow, SageMaker Pipelines, and Airflow.

• Exceptional communication and leadership abilities.

• Experience with big data technologies like Spark and EMR is preferred.

• Familiarity with containerization technologies, including Docker, ECS, and EKS, as well as serverless architecture is preferred.

• A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related discipline is preferred.

• An English proficiency selection is required on the application form.

🏝️ Benefits

• Opportunities for professional growth and career progression.

• Engage with state-of-the-art technologies and industry pioneers in data engineering and AI.

• A collaborative environment that promotes knowledge sharing.

• An equal opportunity employer dedicated to unbiased hiring practices.