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LLM Fine-Tuning & Alignment Specialist — Anthropic
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Generative & Agentic AI · Verified Opening #44

LLM Fine-Tuning & Alignment Specialist

business Anthropic location_on San Francisco, CA (Hybrid) apartment Hybrid Full Time

Compensation

$210K – 300K/yr

bolt Apply for this role
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Published Date

3 weeks ago

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Work Arrangement

Hybrid • San Francisco, CA

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Open Positions

2 openings

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Experience Level

Senior

overview Role Overview

About the opportunity

Advance Constitutional AI, RLHF, and automated prompt red-teaming across Claude model releases.

Anthropic is dedicated to building safe, interpretable, and steerable AI systems. We are seeking an Alignment and Fine-Tuning Specialist to design and execute reinforcement learning from human and AI feedback (RLHF / RLAIF) pipelines that enhance Claude’s helpfulness, honesty, and safety boundaries.
task Core Responsibilities

What you will do

  • check_circle Curate high-quality instruction datasets and formulate constitutional alignment critique principles.
  • check_circle Train and evaluate Direct Preference Optimization (DPO) and PPO alignment models at scale.
  • check_circle Build automated red-teaming agents that probe safety boundaries, prompt injections, and jailbreaks.
  • check_circle Collaborate with interpretability researchers to inspect internal neural activations during reasoning.
verified_user Candidate Profile

What we are looking for

  • arrow_circle_right Strong track record in deep learning with specific focus on Large Language Model fine-tuning and alignment.
  • arrow_circle_right Experience with PyTorch, DeepSpeed, Megatron, DPO, and distributed training clusters.
  • arrow_circle_right Passionate dedication to AI safety, truthfulness, and ethical technology development.
code_blocks Technologies & Competencies

Skills & Tech Stack

RLHF Constitutional AI DPO PyTorch Anthropic Claude Python
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Why candidate applications stand out

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Verified Technical Credentials

Applications include direct proof-of-work repositories and instructor verification endorsements.

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Fast-Track Hiring Visibility

Direct internal referral channels through enterprise partners bypass automated resume discard filters.

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