Solutions Engineer, Labelbox
$140-160k
Data training platform for ML applications
Job no longer available
Data training platform for ML applications
201-500 employees
Job no longer available
$140-160k
201-500 employees
Company mission
To build the best products for humans to advance artificial intelligence.
Role
Who you are
- 4+ years of experience in customer facing technical role
- Proficiency in Python
- Experience with Hugging face or AI model training, data warehouses, APIs
- Experience using Cloud Infrastructure with GCP, AWS, or Azure
- Understanding of the language and technical stacks of ML/infra engineers and data scientists
- As the technical stacks evolve continuously, being curious and a life-long learner is a requirement
- Strong presentation and communication skills, both verbal and written
- Entrepreneurial and problem-solving mindset, experience managing customer challenges and seeing them through resolution
- Technical Bachelor's degree (Computer Science, Engineering, Mathematics)
What the job involves
- Improve customer's experience by providing technical support, sharing best practices, leading technical discussion, discovering use cases, delivering product demos and proof of concept to show the value of Labelbox
- Build trust and establish relationships with the customer teams, helping them realize value from Labelbox, and working backwards from optimal customer experience
- Engage with Product teams to guide them through customer requests and provide input to the roadmap
- Become an expert in Labelbox, and related partner products, as customers will seek your advice and expertise
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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