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Pulsar

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Details

Positions: Full Stack Engineer or ML Engineer Intern
Location: Palo Alto (or Remote)
Innovation Area: Energy Efficiency
Position Type: TomKat Center-supported
Compensation: $7,500
Internship Term: 8 weeks

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We are a team of Stanford engineers, computer scientists and manufacturing experts disrupting the multi-trillion manufacturing industry. Our product combines sensor technology with machine learning to monitor industrial processes in real-time and help factories operate more efficiently. This fully-automated system enables industrial monitoring at a fraction of the cost and implementation time of other solutions. We are backed by the Stanford TomKat Center, StartX accelerator, The MBA Fund and some top Silicon Valley investors, and our system is implemented in several industries including paper, plastics, packaging, metal, food processing, among others.

Responsibilities

We are looking for a Full Stack Developer (Node.js + React & TS) or Machine Learning Engineer to join our team as an Intern. You will work side-by-side with Pulsar founders, and experienced full-stack and machine learning engineers to build new features for our SaaS web application and internal admin tools. The job involves interesting design challenges including a backend for data streaming, real-time analytics, ML data pipelines, among other things.

This is a great opportunity for someone interested in taking a leading role in a fast-growing startup, with the possibility to work full-time afterwards.

Who Should Apply

The ideal candidate is detail-oriented, proactive and excited about being part of an early-stage but highly ambitious and talented startup team.

Required Expertise

For the Full Stack position, previous experience (courses, projects, previous internships) with Node.js for Backend development and React with TypeScript for Frontend development will be highly valued

For the ML Engineering position, an interest in Machine Learning Systems Design & MLOps and/or Time-Series analysis is recommended 

For both roles, familiarity using Unix-based OS Shells and Github for collaboration and version control is required

Preferred Skills/Majors

  • Undergrad majoring in Computer Science, Electrical Engineering or related field