Machine Learning Engineer
Techunting
Buenos Aires y alrededores
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Main responsibilities and duties:
- Stay up-to-date with the latest advancements in machine learning by exploring and drawing insights from state-of-the-art research papers. Leverage this knowledge to design and develop innovative machine learning models tailored to our specific needs.
- Translate conceptual models into practical implementations, utilizing programming languages and machine learning frameworks. Train and fine-tune models to achieve optimal performance and accuracy.
- Drive the deployment process of machine learning models into production environments. Collaborate with cross-functional teams to ensure smooth integration and scalability of the models.
- Apply the best MLOps (Machine Learning Operations) practices and principles throughout the entire modeling workflow. Streamline processes for efficient development, testing, and deployment of machine learning solutions.
- Dive deep into problem domains to gain a comprehensive understanding of challenges and opportunities. Analyze and preprocess data to extract valuable insights for model improvement.
- Propose and experiment with novel ideas and approaches to tackle complex problems. Explore creative ways to leverage data and develop new concepts that could potentially revolutionize the field.
- Collaborate with a team of skilled professionals, including data scientists, engineers, and domain experts. Foster a collaborative environment that encourages knowledge sharing and continuous learning.
- Bachelor degree in Computer Science, Software or Electrical Engineering, or comparable professional experience in Machine Learning related areas.
- Excellent written and verbal communication skills in English.
- Experience working with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, and TFX.
- Experience in technologies like Spark, Kafka, Spark streaming, Flink etc.
- Expertise in MLOps and model integration into larger-scale applications.
- Experience with implementing and scaling feature store across organization.
- Strong programming skills in Python and experience with popular machine learning libraries/frameworks (e.g., TensorFlow, PyTorch).
- Expertise in using Docker and Kubernetes.
- Strong problem-solving skills and ability to analyze and translate business requirements into technical solutions.
- Ability to read, interpret, and apply research papers in machine learning. A strong grasp of foundational machine learning concepts is essential.
- Knowledge of agile methodologies. and ability to work in a fast-paced and evolving environment. Willingness to learn and adapt to new technologies and methodologies.
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Nivel de antigüedad
No corresponde -
Tipo de empleo
Jornada completa -
Función laboral
Ingeniería y Tecnología de la información -
Sectores
Tecnología, información e internet
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