Applied AI Engineer

Salient•San Francisco, CA

9d•$200,000 - $300,000•Onsite

About The Position

We’re building the AI infrastructure powering the future of financial operations - starting with automating the most painful and complex workflows in loan servicing. Backed by a16z and Y Combinator, with $65M raised in Series A funding. 8-figure ARR < 2 years already serving > 20% of the auto lending industry, and processing millions of real customer calls and transactions daily. Fully deployed with major financial institutions - not just PoCs. We are expanding into new financial services segments! In-person office culture in San Francisco, CA. We're fully integrated with our customers, own the full stack, and are moving fast to bring modern AI into regulated industries where precision, reliability, and performance matter most. We’re looking for a Member of Technical Staff to help build the speech and language models behind Salient’s production voice agents. You’ll work on challenging problems in speech and language modeling. Many of these problems look solved in academic benchmarks, but remain deeply unsolved in real-world production. This is a high-ownership role on a small, elite team. You’ll own core parts of the system end to end, and everything you do will have direct revenue impact.

Requirements

Strong engineering fundamentals and ability to build reliable production systems.
Experience with speech modeling, or LLM post-training.
Familiarity with areas such as ASR, TTS, turn detection, speech enhancement, multilingual speech, LLM post-training, or model evaluation.
Ability to diagnose messy real-world model failures and turn them into practical improvements.
High ownership, strong execution speed, and comfort operating in ambiguous technical areas.

Nice To Haves

Prior experience in speech modeling and LLM post-training is ideal, but not required. We care more about slope, intensity, and technical ability than exact background.
Exceptional engineers who are highly driven and excited to work on hard AI problems are encouraged to apply!

Responsibilities

Build and improve production speech models and systems with the ultimate goal of improving real-time conversational quality.
Post-train LLMs for voice agents used for consumer finance.
Develop evals, harnesses, and monitoring systems.
Work across models, data, infrastructure, and product to improve end-to-end agent quality.
Own major technical areas with significant autonomy, from problem definition to production deployment.