Job: Senior Software Engineer (ML Infra)
About the Company:
Our client is an innovator in urban mobility, designing autonomous delivery robots to reduce traffic congestion and minimize carbon emissions. Their technology enables fast and economical deliveries, clearing streets of large vehicles and enhancing energy efficiency. With experience in thousands of commercial deliveries, the company has established itself as a leader in the sidewalk delivery market, backed by top-tier investors and strategic partnerships that ensure a continuous flow of business opportunities.
About the Role:
Our client is looking for a Senior Software Engineer, ML Infra to join their Machine Learning (ML) Infrastructure team. This role involves developing and maintaining ML infrastructure, improving development, management, and deployment processes for ML models, and collaborating with ML engineers to design relevant metrics and algorithms.
Responsibilities:
- Develop and maintain ML infrastructure, including sensor data ETL pipelines, data mining, and continuous training pipelines.
- Develop MLOps systems to manage the lifecycle of cloud training and inference pipelines.
- Collaborate with ML engineers to design metrics to extract relevant sensor data.
- Design and implement algorithms such as collaborative filtering and active learning.
- Work with annotation providers to establish annotation processes, quality control, and feedback loops.
Requirements:
- Experience designing, building, and improving large-volume ML training and validation pipelines.
- Experience building native cloud applications.
- Experience with large-scale data processing pipelines in production.
- Proficiency in at least one of the following languages: C++, Python, or Go.
- Practical knowledge and experience in Computer Vision and Deep Learning.
- A tendency to automate workflows for oneself and others.
- Advanced English proficiency.
- 5 years of experience in the general field of software engineering or ML infrastructures.
Qualifications:
- Experience in designing, building, operating, and improving ML data pipelines.
- Experience with cloud applications.
- Experience with large-scale data processing.
- Deep knowledge of Computer Vision and Deep Learning.
- Ability to automate workflows.
Bonus Points:
- Experience with data discovery and visualization tools like Voxel51, Facets.
- Experience with database systems like BigQuery, MongoDB.
- Experience with the Nvidia Jetson platform, e.g., CUDA, TensorRT.
- Experience with Big Data products such as Apache Beam, Spark, Hadoop, GCP BigQuery, AWS Redshift.
