PlusAI

Builds AI driving systems for commercial trucks

Senior Machine Learning Infrastructure Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeSanta Clara, CA, USA$160k - $200k /yrHybrid

About the Job

Requirements

A PhD or MS in Computer Science, Electrical Engineering, or a related field.
Strong oral and written communication skills.
A PhD new graduate, or a master's degree holder with at least 3 years of software engineering experience focused on machine learning infrastructure or distributed systems.
Proficiency in Python, C++, and SQL.
A deep understanding of containerization, orchestration technologies, distributed machine learning workloads, and experiment tracking tools such as Docker, Kubernetes, multiprocessing, Kubeflow, and MLflow.
Experience deploying and managing resources across multiple cloud platforms, such as AWS, GCP, or on-premises environments.
Proficiency in at least one deep learning framework, such as PyTorch, and data pipeline tools such as Apache Airflow or Prefect.
Strong knowledge of distributed systems, databases, and storage solutions.
Extensive software design and development skills.
Ability to learn and adapt to new technologies and contribute productively.

Responsibilities

Design and develop scalable, high-performance systems for training, inference, deployment, and monitoring of machine learning models at scale.
Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.
Collaborate with machine learning researchers and engineers to identify bottlenecks and improve platform usability.
Implement distributed systems and storage solutions optimized for machine learning workloads.
Drive improvements in CI/CD workflows for machine learning models and infrastructure.
Ensure high availability and reliability of the machine learning platform by implementing robust monitoring, logging, and alerting systems.
Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.
Mentor junior engineers and contribute to a culture of technical excellence.
Perform work in accordance with the company’s Quality Management System requirements and contribute to continuous improvement efforts.
Ensure team compliance with Quality Management System requirements, monitor quality, and drive process improvements.

Desired Qualifications

Familiarity with fundamental deep learning architectures, such as Convolutional Neural Networks and Transformer models.
Experience building large-scale machine learning datasets, MLOps pipelines, and distributed computing frameworks such as Ray.
Experience working with autonomous vehicles or robotics.

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

As a Senior ML Infrastructure Engineer at Plus, you will design scalable architectures capable of handling petabytes of data while ensuring optimal performance for both training and inference phases. You will build robust pipelines for managing model versioning systems and experiment tracking frameworks, which are essential for maintaining reproducibility across experiments. Additionally, you will be responsible for managing large-scale GPU clusters. This role offers unparalleled opportunities—both technically and professionally—for individuals passionate about solving challenging problems using modern cloud-native technologies. Ideal candidates thrive in environments that leverage tools such as Docker containers orchestrated via Kubernetes clusters, seamlessly integrated with state-of-the-art deep learning frameworks like PyTorch or TensorFlow. If you are eager to push the boundaries of what's possible in machine learning infrastructure and contribute to cutting-edge solutions, this position is an excellent fit!

Responsibilities:

Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale.
Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.
Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability.
Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure.
Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems.
Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.
Mentor junior engineers and contribute to a culture of technical excellence
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
Ensure team compliance with QMS, monitor quality, and drive process improvements.

Required Skills:

Phd or MS in Computer Science, Electrical Engineering, or related field
Good oral and written communication skills
Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems.
Proficiency in in Python, C++, SQL
Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on-prem environments)
Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect).
Strong knowledge of distributed systems, databases, and storage solutions.
Extensive software design and development skills.
Ability to learn and adapt to new technologies and contribute in a productive environment.

Preferred Skills:

Familiarity with fundamental deep learning architectures, such as Convolutional Neural Networks (CNNs) and Transformer models
Experience in building large-scale ML datasets, MLOps pipelines, and distributed computing frameworks like Ray
Experience working with autonomous vehicles or robotics

Salary Range:

$160,000 - $200,000 a year

Our compensations (cash and equity) are determined based on the position, your location, qualifications, and experience.

Your opportunities joining PlusAI

Work, learn and grow in a highly future-oriented, innovative and dynamic field.

Wide range of opportunities for personal and professional development.

Catered free lunch, unlimited snacks and beverages.

Highly competitive salary and benefits package, including 401(k) plan.

About the Company

PlusAI

Builds AI driving systems for commercial trucks

PlusAI develops AI driving software for commercial trucks, working with vehicle manufacturers and logistics partners to automate freight transport. Its SuperDrive system combines sensors, onboard computing, and AI models to understand roads, plan maneuvers, and control a truck within defined operating conditions. Truck manufacturers integrate the software into their vehicles, and PlusAI engineers develop and validate the virtual driver for use on freight routes. It also sells autonomous-driving data and development tools through HyperFoundry, and plans to charge for SuperDrive according to truck usage. PlusAI was founded in 2016 and is headquartered in Santa Clara, California.

Company size: 201-500
Company stage: IPO
Headquarters: Santa Clara, CA
Founded: 2016

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