A.I. Research Engineer

JNB Exectant · United States · posted today ago

engineering remote jobs in united states

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About this role

Our Client Company Overview

QOVES is a biomedical startup that focuses on improving patient experiences in cosmetic medical clinics through software. In simple speak, we make software that uses A.I., computer vision, recommendation algorithms and other to predict how patients may look like after cosmetic surgery and to diagnose whether the surgery is even beneficial. Our goal is to turn the process of consultation for cosmetic surgery into a well defined, clinical procedure of diagnosis and visualisation through our software integrations with clinics.

Your Role

In simple terms, you will be in charge of managing the technical development of the product directly under the CTO for A.I. related matters. This involves conducting research into the latest papers and approaches into visualization and generative networks, finetuneing existing products and deploying endpoints to production to work with the rest of the team.

Position: Research A.I. Engineer

Location: Remote / London (preferred), sponsorship possible

Employment Type: Full-timeOur

Culture

We take our work seriously and reap the rewards equally amongst our team. We're after team members that want to strive for the best and be recognised as such in their field:

Curious, intellectual, confident - Team members that are confident in their decisions; a self-assured confidence that comes from years of experience and independent research. You're able to call out wrong decisions and stand behind your own with conviction.
Work hard, play hard we often have to work 60+ hour weeks and expect the same from our team. When it needs to be done, we do it but in return we recognise and reward team players for their dedication to the craft.
Meritocracy, always you own and earn your destiny. The best argument wins, not the loudest voice or the most senior team member.

Why Work at QOVES

We're solving a real problem with real implications - the healthcare system is overworked, A.I. integration will help dramatically ease the triage burden.

We have the resources to achieve our mission. We have raised a sizable seed round backed by local and foreign investors to fund our product development.

We are developing cutting-edge AI technology. The systems being built rely on our latest internal and external research in generative and computer vision fields to accurately diagnose medical anomalies from photographs of patients. Succeeding here will provide you a strong backing into future companies leveraging these A.I. discoveries to build newer products.

We have an endless supply of customers and interest. With our social platforms getting 40 million+ unique viewers a month, the top celebrity doctors on our waitlists and endless celebrities as our current customers, we've built enough influence in our field over 4 years to be the largest in solving the facial diagnostic problem. We have the head start to reach the multiple billions.

Work with two established founders to solve a generational problem.

Your Role to Shape QOVES

At QOVES as a Founding AI Engineer, you will help build the most advanced AI facial diagnostic pipeline in the world. It's no easy task but you won't be alone!

Your qualifications

You have demonstrated the ability to build world-class AI/LLM applications, with a strong emphasis on building visualisation systems (GANs, Diffusion Models...):

3+ years of work experience deploying LLM/ML models to production
Technical experience with visual generative models, especially in Generative Adversarial Networks.
Degree in Computer Science, Engineering, AI, Math, Physics, or similar or equivalent additional work experience
Excellent communication skills to interact with founding team and customers
Ability to understand and implement technical state-of-the-art research papers
Proficiency to write production-level code for AI/LLM based applications
Proficiency with advanced Python workflows, including (Pytorch + Langchain/LlamaIndex or similar libraries, Scikit-learn, pandas)
Proficiency with version control (Git)
Experience implementing pipelines for visualization models (GANs, Diffusion Models)
Ability to prototype and explore new generative A.I. solutions quickly
Experience implementing predictive machine learning models
Experience implementing open source LLMs (from Hugging Face, Github, ...)
Experience with GPU management for LLM deployment
Experience with fine-tuning LLMs