Applied AI Engineer — Production ML for Marketing Automation

Different Inc.; San Francisco (CA); On-site; USD 145,000 - 285,000; Full time

Job summary

Different Inc. is hiring a senior ML-focused engineer to build agents, evals, and model systems that power production-grade marketing automation. You will translate research into reliable production code, design end-to-end workflows, and optimize for quality, latency, and cost in a live product.

You’ll work on agents, content generation, evaluation metrics, context management, and learning from outcomes to continuously improve decisions in a fast-moving marketing stack.

Qualifications

• Strong ML fundamentals and experience building with modern LLMs beyond a prototype.

Responsibilities

• Build multi-step workflows that turn a marketer's goal into concrete actions (Agents and tool use).
• Improve the quality of ads, emails, landing pages, and other marketing content produced by the system (Generation).
• Define what good looks like, measure it, and use results to improve the system (Evals).
• Decide what a model needs to know at each step, what should be remembered, and what should be retrieved (Context and memory).
• Use marketer edits, feedback, and campaign results to improve future decisions (Learning from outcomes).
• Decide when the system should try something new and when it should stick with what is working (Exploration).
• Choose, route, and fine-tune models balancing quality, latency, and cost (Model systems).

Skills

ML fundamentals

Production reliability

Experimentation to production

Judgment on new techniques

Long-horizon reasoning

Education

BS/MS in CS, ML, Math or related field

MS/PhD useful but not required

Tools

RAG/memory systems

Model routing and inference optimization

Evaluation pipelines

Job description

Different Inc. is hiring a senior ML-focused engineer to build agents, evals, and model systems that power production-grade marketing automation. You will translate research into reliable production code, design end-to-end workflows, and optimize for quality, latency, and cost in a live product.

You’ll work on agents, content generation, evaluation metrics, context management, and learning from outcomes to continuously improve decisions in a fast-moving marketing stack.