Software Engineer, ML Infrastructure

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

What you'll be doing

AI/ML is a core part of our autonomy. Our ML infrastructure empowers us to train and test all kinds of ML models for various real-world tasks. We also use it to mine useful data from terabytes of sensor recordings that we capture every day. As we rapidly grow our fleet of robots and expand into new cities we are scaling our investment in ML infrastructure.

We are looking for an engineer who will join our Machine Learning Infrastructure (ML Infra) team on a mission to build and improve this platform.

Responsibilities

• Develop and maintain highly scalable data processing pipelines for data curation, annotation, search and ml feature extraction.

• Build and improve our active learning pipelines. Ensure the scalability of our training jobs and inference endpoints.

• Develop and maintain our orchestration and scheduling systems.

• Collaborate with autonomy engineers to build new features for our autonomy data platform, improving data accessibility and developer productivity.

• Build integrations with annotation providers to efficiently annotate large scale datasets

• Develop infrastructure components using IaC(Infrastructure as Code) and implement CI/CD processes to streamline ongoing development of the platform.

• Develop monitoring and alerting frameworks to ensure platform reliability, stability and cost efficiency.

• Collaborate with ML Engineers in accelerating the ml development velocity.

• Work with the data team to ensure SLAs around data quality and availability. Optimise storage costs by tuning retention policies and improving data access patterns.

Qualifications

• BS or MS in computer science (or equivalent work experience) with focus in data engineering and machine learning

• 2+ years of industry experience developing big data processing and/or machine learning pipelines

• 1+ years of hands on experience with cloud platforms (AWS/GCP/Azure)

• Proficient in Python

• Solid understanding of system design fundamentals and distributed computing concepts

What makes you standout

• Experience with terabyte scale data

• Experience with orchestration engines like Airflow, Prefect

• Experience with data discovery tools and methodologies like RAG, Vector Search

• Experience with databases. E.g BigQuery, Postgres, MySQL, MongoDB.

• Experience with vector search databases. E.g MongoDB Atlas, Pinecone,

• Experience with IaC and CI/CD. E.g Terraform, Jenkins, Github Actions

• Experience with big data frameworks such as Apache Spark/Beam/Hadoop