Senior Machine Learning Engineer Remote

Responsibilities

• Contribute to the refinement, establishment, and operational lifecycle of ML pipelines using industry best practices
• Design, create, maintain, troubleshoot, and enhance steps in ML pipelines
• Own and contribute to the design and execution of ML prediction endpoints
• Collaborate with System Engineers to establish an ML lifecycle management environment
• Draft specifications, documentation, and user guides for developed applications
• Support the enhancement of coding practices and organization of scientific work cycle repositories
• Set up pipelines for different projects
• Regularly identify technical risks and gaps and formulate risk mitigation strategies
• Collaborate with data scientists to transition predictive models into production, creating scalable data preparation pipelines, and understanding model scopes and purposes

Requirements

• Minimum of 3 years of experience as a Machine Learning Engineer or in a similar capacity
• Strong proficiency in programming languages, particularly Python
• Solid grasp of Data Science principles and Machine Learning Engineering model creation experience
• Expertise in Engineering Best Practices
• Comprehensive understanding of Machine Learning fundamentals
• Hands-on experience implementing Data Products using technologies like the Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML) or equivalent technologies
• Experience with Big Data technologies such as Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc
• Experience with automated data pipeline and workflow management tools like Airflow, Argo Workflow, etc
• Familiarity with different data processing paradigms (batch, micro-batch, streaming)
• Practical experience with one or more major Cloud Providers such as AWS, GCP, or Azure
• Experience with at least one MLOps-related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI/AI Platform, Databricks MLOps-related tools/technologies like MLFlow, Kubeflow, TensorFlow Extended (TFX)
• Experience integrating ML models into complicated data-driven systems in a production environment
• Fluent in English with a B2+ level

Nice to have

• AWS, GCP, or Azure Certified would be a significant advantage
• Aptitude for rapidly adapting and applying new technologies
• Experience in a startup/environment, demonstrating the ability to deal with ambiguity