Job Description:
Theta Lake is the only communication compliance vendor directly financially backed by the leaders in unified communications including funding by Zoom, Salesforce, RingCentral, and Cisco as well as Wells Fargo and tier 1 venture firms including Battery, Lightspeed, and Neotribe. Theta Lake is also the only vendor with a 5 out of 5 star and a 100% Would Recommend ratings for enterprise information archiving from customers via Gartner Peer Insights as well as the only vendor with patents for unified communication compliance and security. Theta Lake works with security focused and regulated organizations to solve their communication capture, archiving, proactive compliance risk detection, and surveillance needs.
Read more: https://thetalake.com/
The Position
As Senior NLP Engineer you’ll be part of Theta Lake’s Data Science team, building and improving the models and pipelines that turn messy, multi-modal communication into structured, reviewable signals. As a senior individual contributor with significant autonomy, you’ll own the full lifecycle of your work, from data collection and modelling through prototyping, coding, and delivery to production. You’ll apply both classical ML and modern LLMs to the problem and develop new methods to address it.
You’ll work closely with product, other engineering teams, and customer-facing teams to understand how risk detection actually gets used, and to make sure what you build solves real customer pains.
Location and How to Apply
Fully Remote – But prefer home location based in the UK
We cannot sponsor visas at this time. Please do not apply if you are on a visa for the UK
To apply, please contact us at careers@thetalake.com
Responsibilities:
- Own NLP problems end to end. Take detection and analysis problems from data collection and labelling through modelling, prototyping, and production delivery, and stay responsible for how they perform once they're live.
- Use LLMs in products and as leverage. Build them into customer-facing features, and use them to develop tooling and streamline how the team works.
- Build across the modality range. Work on the full pipeline that turns voice, video, images, and text into analyzable signals, including the OCR, speech-to-text, and preprocessing steps upstream of the models themselves.
- Operate at production scale. Build models and pipelines that run reliably and efficiently against very high volumes of communication data.
- Be a good colleague. Generous with your time and knowledge, open to being wrong, and easy to work alongside.
Preferred Qualifications:
- Strong NLP background, with a track record of building and shipping models that made it to production and stayed there. Deep understanding of machine learning fundamentals. Hands-on experience with both classical ML and modern LLMs. Experience with noisy, real-world data.
- Solid software engineering fundamentals. Experience with software processes in a multi-developer environment: requirements, demos, source code control (git), defect tracking (jira), estimation and planning, build, test automation, CI/CD, etc. Fluency in Python and its ML/NLP ecosystem.
- Product sense and communication skills: you can work with non-technical stakeholders and make sound calls about what's worth building.
- A love of language and how people use it. You find the quirks of real human communication genuinely interesting, and you're the kind of person who notices how things are said, not just what's said.
- Bonus: experience in compliance, RegTech, finance, or another regulated domain. Fluency in other (human) languages.