TextUs

Technology

SeniorMLEngineer

$180–200k Denver, Colorado, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior ML Engineer at TextUs. Skills: ML platform, ML Ops, Applied ML, LLM. Own ML and AI engineering layer. Build ML Ops platform”

What You'll Achieve.

Ship ML systems with rigor; Catch regressions before prod; Stay inside cost budgets; Stay inside latency budgets; Make features measurably better

Industry & Context.

Technology
Problems you'll solve

Root cause analysis; Troubleshooting; Build-vs-buy decisions

Eligibility Requirements

On call for models

What They're Looking For.

Must Have

6+ years engineering experience, 3+ years ML platform experience, 3+ years ML Ops experience, 3+ years applied ML production experience, On-call for models experience, Applied LLM experience, Comfortable in Python, Comfortable in Ruby on Rails, Cloud-native infrastructure depth, Build-vs-buy decisions track record, Clear communicator

Nice to Have

Real fine-tuning experience, Conversational AI experience, NLP experience, Messaging products experience, PII handling experience, Data governance for ML experience, Background in smaller engineering org

What You'll Do.

Own ML and AI engineering layer

Build ML Ops platform

Build deployment pathways

Build evaluation infrastructure

Build drift detection

Build cost monitoring

Build latency monitoring

Build rollback patterns

Build progressive rollout patterns

Build LLM-powered features

Build structured generation

Build eval frameworks

Manage latency budgets

Build human-in-the-loop feedback

Build specialized classifiers

Build inference infrastructure

Make build-vs-buy calls

Build guardrails for engineers

Define data usage policies

Generate synthetic eval

Detect regressions automatically

Speed up experimentation

Help engineers add AI features

How You'll Work.

Team & Collaboration

Cross-functional teams; Product engineers

Communication Scope

Explain model behavior; Explain inference pipeline

Full Job Description

WHY TEXTUS TextUs on a mission to revolutionize business communication by enabling seamless and impactful engagement between workers and consumers. With a focus on innovation, ease of use, and delivering measurable results, our strategy is rooted in creating tools that outperform other messaging solutions while fostering trust and value for our customers and stakeholders. At TextUs, every team member is empowered to make a difference. Our collaborative and data-driven culture, combined with the guidance of a proven leadership team, ensures you have the resources and support to excel. Together, we’re building the future of mobile-first, conversational engagement and redefining what’s possible for businesses and their stakeholders. RESPONSIBILITIES We're moving from a product where AI is a feature you can turn on to one where it's a layer that runs through everything: response suggestions, abuse detection, summarization, lead scoring, intent classification. That shift only works if there's an engineering layer underneath that treats ML systems with the same rigor as the rest of production. We're AI-pragmatic, not AI-maximalist. Most of what we ship will run on frontier model APIs with retrieval and good prompt engineering. Some will run on small classifiers we train ourselves. A few things will justify fine-tuning against our eleven years of conversation data. Your job is to know which is which, and to build the platform that lets us move between them without rebuilding from scratch every time. You own the ML and AI engineering layer end to end. The ML Ops platform: Model registry, feature pipelines, and deployment pathways that any engineer in the org can use Evaluation infrastructure that catches regressions before they hit prod, not after Drift detection, online evals, cost and latency monitoring Rollback and progressive rollout patterns built for ML systems, not retrofitted from generic CD Applied AI in the product: LLM-powered features built on frontier APIs: pro

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