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12 часов Π½Π°Π·Π°Π΄

Member of Technical Staff - Agent Engineer (AI)

200Β 000 - 300Β 000$
Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
onsite
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Английский
b2
Π‘Ρ‚Ρ€Π°Π½Π°
US
Вакансия ΠΈΠ· списка Hirify.GlobalВакансия ΠΈΠ· Hirify Global, списка ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… tech-ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ
Для мэтча ΠΈ ΠΎΡ‚ΠΊΠ»ΠΈΠΊΠ° Π½ΡƒΠΆΠ΅Π½ Plus

ΠœΡΡ‚Ρ‡ & Π‘ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄

Для мэтча с этой вакансиСй Π½ΡƒΠΆΠ΅Π½ Plus

ОписаниС вакансии

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TL;DR
Member of Technical Staff - Agent Engineer (AI): Building and evaluating production AI-agent systems for biomedical discovery with an accent on agent harnesses, tool use, planning, memory, and multi-agent coordination. Focus on designing rigorous evaluations, improving reliability and performance, and operating long-running scientific workflows with safe execution and subagents.

Location: South San Francisco, United States; on-site

Salary: $200,000–$300,000 per year plus equity

Company

hirify.global is an applied research lab building agentic intelligence to accelerate biomedical discovery.

What you will do

  • Advance the agent harness by productionizing research and open-source developments in multi-agent coordination, model routing, memory, planning, and tool use.
  • Build evaluations that measure agent quality, reliability, latency, and cost on representative scientific tasks.
  • Monitor production agent quality, troubleshoot failures, and translate findings into engineering improvements.
  • Collaborate on infrastructure for long-running sessions, sandboxed execution, background work, and subagents.
  • Partner with scientists and engineers to evaluate and productionize new agent capabilities.

Requirements

  • Strong software engineering experience with production backend systems, infrastructure, or distributed systems.
  • Research or production experience in machine learning or another quantitative discipline.
  • Familiarity with LLM APIs, tool calling, agent runtimes, or workflow orchestration.
  • Strong quantitative judgment and the ability to assess whether improvements are real, reproducible, and meaningful.
  • Ability to move between research questions, data analysis, system design, and production implementation.
  • Experience or strong interest in AI for science, scientific agents, computational research, or automated scientific discovery.

Nice to have

  • Experience with LLM evaluations, human evaluation, model judges, replay testing, benchmark design, or experiment tracking.
  • Experience applying classical machine learning methods alongside LLMs in production systems.
  • Experience with task queues, event streams, Kubernetes, code sandboxes, or durable workflow systems.
  • Advanced degree or equivalent experience in machine learning, computational biology, physics, applied mathematics, statistics, or a related field.

Culture & Benefits

  • Equity participation in building biomedical discovery technology.
  • Full medical, dental, and vision coverage, including therapy sessions and an eyewear stipend.
  • 401(k) and unlimited PTO for US employees.
  • Lunch and snacks in the office, regular team offsites, and company events.
  • Fast-paced culture focused on excellence, speed, and collaboration.

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’