2027 Intern - AI/ML Engineer, Autonomous Vehicle ML Infrastructure

Description

The company's autonomous vehicle machine learning infrastructure team builds the platform that ML engineers use for experiments, serving use cases in areas such as embodied AI, simulation and data science.

The team's work covers three areas: AI validation and inference, which runs large simulation workloads and dependable inference pipelines; ML compute, which speeds up large training and inference jobs across cloud and on-prem resources; and AV pipelines and lineage, which automates workflows on an orchestration platform and tracks data and model lineage.

The work supports the company's path to commercializing autonomous driving.

As an intern, you will help improve data processing pipelines, job scheduling, and the speed of training and inference, and you may work on test infrastructure such as Carbench and HIL. You will support tool building, instrumentation and monitoring to raise reliability, cut latency and shorten iteration cycles.

Responsibilities

• Build scalable infrastructure and tools for training, operating and running inference on regression and rules-based models.
• Gather and synthesize requirements, suggest improvements, and help shape a feature roadmap.
• Write code for deliverables alongside the engineering team.
• Adapt standard machine learning methods to run well on parallel hardware such as distributed clusters, multicore SMP systems and GPUs.
• Take on other tasks that vary by team.

Requirements

• Be currently enrolled full-time in a degree program and working toward a Bachelor's or Master's in computer science or a closely related technical field.
• Have experience with systems software or algorithms.
• Have experience programming in modern object-oriented languages such as Java, C++ or Python, and in at least one of Java, C/C++, Perl, PHP, Go or Python.
• Communicate well and have worked with cross-functional teams.
• Be able to work full-time, 40 hours per week.
• Preferred: Have shown software engineering work through an internship, a job or coding competitions.
• Preferred: Be familiar with AI-assisted engineering tools for code generation, model analysis or experiment planning.
• Preferred: Show creativity and solve problems quickly.
• Preferred: Have research or work experience in machine learning infrastructure.
• Preferred: Have experience with Hadoop, HBase or Pig, or with MapReduce, Sawzall or Bigtable.
• Preferred: Have experience with distributed systems such as Spark, Ray, Kubernetes or Slurm.
• Preferred: Have experience with scheduling algorithms, orchestration or compute resource management.
• Preferred: Plan to return to your degree program after the internship.
• Preferred: Expect to graduate between December 2027 and August 2028.

Conditions

The role is based in Sunnyvale, California.

The hybrid schedule requires up to three office days per week, or as the team decides.

The monthly salary range is $9,600 to $11,800.

Eligible students selected for the 2027 Student Program receive a one-time lump sum stipend, which is taxable.

The company aims for a workplace free of unlawful discrimination that also fosters inclusion.

Benefits

• Paid US company holidays.
• A vehicle discount program for you and your family.
• Room to grow within the company based on results.
• Intern events for meeting company leaders and fellow interns.