We are looking for an experienced software Engineer to join our AI group and build our next generation Machine learning infrastructure and enable the research and development of new models.
What will you do?
Work closely with data scientists, data engineers and other stakeholders to streamline, implement and optimize our machine learning models and data pipeline infrastructure.
Design and build automated pipelines and tools for model training, testing, validation, and deployment to ensure smooth and efficient operations.
Manage infrastructure requirements for machine learning projects, including cloud resources, container orchestration (e.g., Kubernetes), and distributed computing systems.
Build and maintain monitoring and alerting systems to proactively identify the models performance and bottlenecks and optimize the systems speed, scalability, and cost.
What will you do?
Work closely with data scientists, data engineers and other stakeholders to streamline, implement and optimize our machine learning models and data pipeline infrastructure.
Design and build automated pipelines and tools for model training, testing, validation, and deployment to ensure smooth and efficient operations.
Manage infrastructure requirements for machine learning projects, including cloud resources, container orchestration (e.g., Kubernetes), and distributed computing systems.
Build and maintain monitoring and alerting systems to proactively identify the models performance and bottlenecks and optimize the systems speed, scalability, and cost.
Requirements:
B.Sc. in Computer Science/ Engineering/ Mathematics, or any other quantitative field
3+ years of hands-on experience with data engineering: transformation, analysis, and management using ETL processes.
Experience with cloud platforms like AWS, GCP, or Azure
Proven experience in building and deploying software systems
Familiarity with containerization technologies like Docker and Kubernetes a plus
Experience with distributed computing frameworks like Spark or Ray is a plus
Strong understanding of machine learning concepts and their computational requirements
A passion for building high-quality, maintainable code
Effective communication and collaboration skills.
B.Sc. in Computer Science/ Engineering/ Mathematics, or any other quantitative field
3+ years of hands-on experience with data engineering: transformation, analysis, and management using ETL processes.
Experience with cloud platforms like AWS, GCP, or Azure
Proven experience in building and deploying software systems
Familiarity with containerization technologies like Docker and Kubernetes a plus
Experience with distributed computing frameworks like Spark or Ray is a plus
Strong understanding of machine learning concepts and their computational requirements
A passion for building high-quality, maintainable code
Effective communication and collaboration skills.
This position is open to all candidates.
