Applied AI Research Engineer

Archer; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Unlimited PTO

Medical/Dental/Vision benefits

Retirement plan eligibility

Parental leave

Fertility and family building benefits

Lunch and snacks

Job summary

Sierra is partnering with Archer to recruit for a role focused on building and deploying production ML/AI systems that power customer-facing agents. You will work on post-training methods, voice AI, and long-horizon task execution, turning complex problems into actionable ML tasks and evaluating outcomes with real-world impact.

The position emphasizes cross-functional collaboration, data-driven experimentation, and scalable model development across text and audio domains in a primarily in-person

Qualifications

• Strong experience building and deploying production ML/AI systems.
• Judgment in framing product problems as ML tasks and selecting effective approaches.
• Experience with data, experimentation, evaluation, and model iteration.
• Evidence-driven approach to ML with good judgment on modeling vs simpler solutions.

Responsibilities

• Tackle applied AI/ML problems; push post-training, voice AI, long-horizon task execution.
• Determine when to build models vs use frontier intelligence; balance quality, speed, cost.
• Turn ambiguous product problems into well-framed ML problems.
• Develop, fine-tune, evaluate, and deploy models for customer-facing AI agents.
• Advance post-training work toward RL and long-horizon optimization.
• Build evaluations linking model performance to real-world agent quality.
• Work with large-scale proprietary datasets across text and audio.
• Collaborate across teams from experimentation to production deployment.

Skills

ML Systems

Problem Framing ML

Data Experimentation

Evidence-driven ML

Cross-stack Work

Values Alignment

CS Degree or Experience

Education

CS Degree or related field

Job description

Sierra is partnering with Archer to recruit for a role focused on building and deploying production ML/AI systems that power customer-facing agents. You will work on post-training methods, voice AI, and long-horizon task execution, turning complex problems into actionable ML tasks and evaluating outcomes with real-world impact.

The position emphasizes cross-functional collaboration, data-driven experimentation, and scalable model development across text and audio domains in a primarily in-person