Software Engineer, Applied AI Research
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 16h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 65d ago
The date the source published, not the day we noticed it (2026-08-28). Last seen at its source 2h ago.
We have tracked this listing since 12 Oct 2026 (20 days). The employer's own board has carried it every time we have read it, most recently 2 hours ago.
Is it remote?
Remote (North America)
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
North America
The description states no restriction of its own. This is the source's own tag.
Pay
$180k–400k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 20d ago · last seen 2h ago
The listing
About the Role
We’re looking to add applied AI research engineers to the team. The ideal candidate will have strong probabilistic and quantitative thinking, the ability to be highly creative and experimental with LLM applications, and ground their work in potential customer and product applications.
Our applied research team focuses on finding new and innovative techniques to improve the frontier of what is possible in agentic AI marketing applications, with a particular focus on image and video. We focus less on theory or writing research papers, and more on experimenting, prototyping, and exploring new methods for applying generative AI to help our customers grow their companies.
Example workstreams include:
Quickly iterating and developing proofs of concept (POCs) to explore the maximum potential of integrating AI into data and marketing workflows
Design and develop evaluation and improvement systems that can make advancements autonomously
Expanding the frontier of what is feasible with AI generated video (e.g. making generated humans maximally realistic)
Experiment with different approaches for generating brand assets that stay aligned to a particular company’s look and feel
We're seeking talented, intellectually curious, and motivated individuals interested in exploring the forefront of AI. While no prior experience with LLMs and AI is required, strong technical skills, particularly in backend architecture or probabilistic systems, and product intuition are essential for understanding and executing these projects from start to finish.
This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation.
Interview Process
Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense and creativity with LLMs, ability to architect backend systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.
Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit.
System Design Screen [60m]: Designing a data processing or machine learning feature end-to-end (depending on background).
Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.
Agent Building Systems Interview [75m]: Work with the interviewer to architect an agentic system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.