Forward Deployed Engineer Intern, Labelbox
This is a paid internship with an hourly rate of $50-$70 per hour
2 days a week in office
Data training platform for ML applications
Be an early applicant
Data training platform for ML applications
201-500 employees
Be an early applicant
This is a paid internship with an hourly rate of $50-$70 per hour
2 days a week in office
201-500 employees
Company mission
To build the best products for humans to advance artificial intelligence.
Role
Who you are
- We care more about how you think than about a specific list of credentials. The things below are what tend to make interns successful in this role:
- Strong Python skills, especially for data work. You should be comfortable picking up a messy dataset and figuring out what is in it
- Familiarity with LLMs from hands-on experience, not just coursework. You have built something with them and have iterated on prompts to make them do what you want
- Strong analytical thinking. You can look at data, spot what is off, and ask the right questions about whether a result is real or noise
- Strong written and verbal communication. You can write a clear update, explain technical work to non-technical stakeholders, and ask a well-formed question when you are stuck
- You finish what you start. When you take on a task, you see it through to the end - including the parts that are not interesting
- Fast learner. The tools, frameworks, and benchmarks you will encounter change quickly. You pick them up without being walked through them
- High agency and ownership. You take responsibility for your work, push it forward without being prompted, and flag issues early rather than late
- Currently pursuing a Bachelor's or Master's in Computer Science, Engineering, Mathematics, or a related technical field
- Genuinely curious about AI and how frontier models are built
- You like being the person who turns “we should look into this” into something concrete
- You work independently and communicate generously. You move fast on your own
- Receptive to feedback
What the job involves
- As a Forward Deployed Engineer Intern, you will work alongside a senior FDE on real client engagements with leading AI labs. You will own concrete pieces of those engagements - writing scripts to process and analyze data, building automated quality checks, and helping validate that the data we deliver is good enough to ship. The work is hands-on, fast-paced, and rarely arrives with a complete spec
- This is not a shadowing internship. You will be expected to take ownership of your projects, work through ambiguity with your manager, and ship work that real clients depend on. If you do well, you will see your work translate directly into how frontier AI models are trained and evaluated
- Labelbox builds the data infrastructure behind frontier AI development. We work with leading research labs and enterprises to produce the high-quality datasets used for evaluation, supervised fine-tuning, and reinforcement learning
- The Frontier AI team you will be joining sits at the intersection of engineering and applied research, working directly with AI lab partners on some of the most demanding data problems in the industry
- Work alongside a senior FDE on live client engagements, owning specific workstreams end-to-end
- Write scripts to process, transform, and analyze data for client deliverables
- Build automated quality checks and serve as a second set of eyes on the data we ship
- Take ambiguous, partially-defined requirements and turn them into something concrete
- Read existing code, extend it, and improve it - most of what you build will plug into systems that already exist
- Drive your work forward without needing daily check-ins. Proactively share progress, flag blockers, and ask for input when you need it
- FDE work at Labelbox is a spot where it spans engineering, research, and direct client work. As an intern, you will get exposure to all three - and to the kinds of problems that most engineering internships do not touch. You will work with people who care about getting the technical details right and who will give you the room to do the same
Our take
Labelbox offers a web service and API helping companies better manage the process of annotating and labelling data used for machine learning (ML). This reduces costly and labour-intensive human data labelling, a major stumbling block for the increasing number of larger companies looking to deploy ML at scale.
Labelbox offers automated labelling as a means of boosting productivity, which puts it in direct competition with Scale AI, a company valued at over $7 billion. Founded in 2018, the relatively young Labelbox will have to find a compelling way of distinguishing itself, such as by addressing the ethical issues faced in data labelling. The company emphasises that its product addresses the problem of bias by working as a sort of auditable record, and offers quality assurance systems to help identify it.
Labelbox has remained focused on streamlining its capabilities to raise its value in line with the rapidly growing market. The company's global expansion efforts have significantly widened its potential client base. The company has also collaborated with Google to make access to its platform easier.
Freddie
Company Specialist at Welcome to the Jungle
Insights
46% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Jan 2022
$110m
SERIES D
Feb 2021
$40m
SERIES C
Total funding: $188.9m
Company benefits
- Flexible vacation policy (we don't count PTO Days)
- 401k Program
- College savings account
- HSA
- Daily lunches paid for by the company (especially convenient while working from home)
- Virtual wellness and guided meditation programs
- Dog-friendly office
- Regular company social events (happy hours, off-sites)
- Professional development benefits and resources
- Remote friendly (we hire in-office and remote employees)
Company HQ
Mission District, San Francisco, CA
Leadership
Brian Rieger
(Co-Founder)Began as an Engineering Intern at Hudson Technologies. Co-founded Infinity Aerospace. Was an Aerodynamics Engineer at Boeing. Worked in Data Science for World Fuel Services.
Manu Sharma
(Co-Founder & CEO)Masters in Astronautical Engineering from Stanford. Founder & CEO of Nuovo Wind. Founder & CEO of Ardulab/Infinity Aerospace. Worked at DroneDeploy for over 3 years, from Drone Engineer to Product Manager. Was a Product Manager at Planet.
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