Machine Learning Engineer

We are looking for an experienced Machine Learning Engineer to join Xmartlabs, a boutique Product Development Studio with offices in San Francisco and Montevideo. 

Requirements:

• 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. 

Responsibilities:

• 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. 

Time Shift: Full time.

Location: Remote