Job description
Head of AI (Start-up / Oil & Gas)
$350,000 - $500,000 + Generous Equity + Full Health Benefits + PTO + Progression in leadership
Fully Remote - Occasional travel to Houston
Perfect opportunity to join an early-stage start-up, where you'll take full ownership of AI starting as an individual contributor and progressing to build and scale your own team from the ground up!
Join a top VC-backed, AI-native start-up preparing for its Series A, with early equity on offer and the chance to make a huge impact from day one!
Founded five years ago, this well-backed start-up is developing a product set to transform the oil and gas industry. Backed by a founding team of industry experts, they are now seeking an AI expert to drive their next stage of growth.
As the AI expert, you will be responsible for leading early-stage builds and deployments. This will include end-to-end AI/ML engineering such as coding, fine-tuning, model optimization, RAG, workflow automation, and the development of secure B2B AI platforms. A key part of your responsibility will be to translate technical AI developments into meaningful business outcomes to VC's and customers, particularly within the oil, gas, and energy sectors.
This is the ideal opportunity for a top tier AI lead or head looking for a new challenge from early stages but with a company offering great equity and the chase to scale a team of your own!
The Role:
*Head of AI / AI lead
* Building and scaling AI for an early-stage start-up with Oil & gas!
* Individual contributor but will move into scaling and leading a team!
* End-to-End AI/ML Engineering (coding, training, fine-tuning, and deploying)
* Model Optimization (model compression, pruning, and sparsification)
* Become the face of AI communicating key milestones with VC, internal teams and customers!
* Remote - Travel required to Houston occasionally
The Person:
* Proven experience in a credible start-up environment.
* Comfortable as an individual contributor, hands-on with building and deploying AI.
* End-to-end AI/ML expertise, including coding, training, fine-tuning, and deployment.
* Solid experience in model optimization, including compression, pruning, and sparsification.
* Strong foundation in data engineering and/or data science.
* Experience with RAG and building or deploying enterprise AI platforms.
