Senior Research Engineer

As a Senior Research Engineer at Unlikely AI, you’ll assist in delivering model prototypes to production. You’ll play a key role in product delivery and designing and implementing new ML features on our platform, which typically includes managing model deployments and ensuring stability. Other projects could include optimising our vector search capabilities. 

Unlikely AI is a deep tech startup working to create a world where highly intelligent automated systems enable humanity to flourish and benefit us all. We are pioneering transformative technology aimed at making Artificial Intelligence more accurate, trustworthy and safe. Based in London, the company was founded by William Tunstall-Pedoe, best known for his key role in the creation of Alexa following the acquisition of his first start-up by Amazon in 2012.

Why Join Us?

Team - We have a world-class team of intelligent, focused, collaborative people. We're ambitious, move fast and have a lot of fun while doing it.

Vision - We have a huge vision for the future. This offers a unique opportunity to work on the foundational layers of AI but, unlike many other companies, we're not just scaling LLMs, we're focused on a novel neuro-symbolic approach.

Tech - You'll work with our novel and cutting-edge tech. Driving this forward involves solving some exciting challenges, so our team has the freedom to be creative and explore innovative ideas in an environment where our technology is evolving and maturing.

What you'll do:

Deploy, monitor, and optimise deep learning models (LLMs)

Design and implement deep learning features and optimise for latency and accuracy.

Collaborate with teams to communicate complex solutions effectively.

Manage and analyse large datasets while ensuring data integrity.

Requirements:

5+ years of experience as a Research Engineer with strong expertise in Python, PyTorch, or TensorFlow.

Proficiency in deploying deep learning models, including experience with technologies like Torchserve, Sagemaker, or VertexAI.

Solid understanding of MLOps practices, including containerisation with Docker, and experience working with cloud infrastructure (AWS, GCP, or Azure).

Hands-on experience optimising model deployments for performance, with a focus on latency and throughput.

Expertise in fine-tuning models for enhanced performance.

Knowledge of NLP, LLMs, and transformer architecture.

Desirable Skills:

Experience building CI/CD workflow development.

Knowledge of retrieval-augmented generation and vector search optimisation.

Experience with infrastructure-as-code tools like Terraform.

Please see our Company Principles to understand the core things we value – in particular, we are looking for exceptional people who are willing to tackle some of the most difficult technical problems there are, in order to create something extraordinary with huge impact.

Location:

We are currently operating a hybrid scheme with a small office near Holborn tube station available to anyone who wants to work there. We also have occasional team days where everyone meets face to face and days where people work heads down from home, communicating with colleagues using Slack and Zoom.

Compensation:

Compensation will be through salary and generous share options. The company has a tax-efficient EMI share option scheme set up (not available to larger companies) which allows us to provide real exposure to the success of the company without taxes being due when they are paid.

Equal Opportunities:

We are committed to having a truly diverse team where everyone is encouraged to be their authentic selves. We, therefore, do not discriminate in employment based on gender, race, religion, sexual orientation, national origin, political affiliation, disability, age, marital status, medical history, parental status or genetic information. Having a broad mix of people helps us to be the best we can.