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Manager Rlhf Jobs in Edison, NJ (NOW HIRING)

Deep understanding of Data preprocessing, Prompt management, Caching, Validation, Advanced RAG, RLHF, and success measurement. * Thorough understanding of LLMOps, data pipelines and other common ...

Strong stakeholder management and technical leadership skills. Preferred * Multi-agent orchestration experience. * AI evaluation and governance frameworks. * Fine-tuning, RLHF, or model optimization ...

Delivery Lead

New York, NY · Remote

$110K - $140K/yr

... RLHF, annotation, model evaluation) * STEM background or strong technical fluency * Python & REACT working knowledge * Experience managing distributed contributor workforces at scale * Background in ...

Senior Research Engineer

New York, NY · On-site

$180K - $200K/yr

There is no middle management. There are no layers of approval. The company is designed, from the ... Spearhead pre-training and post-training efforts, including RLHF, DPO, RLAIF, and other alignment ...

AI Engineer

New York, NY · On-site

$200K - $300K/yr

Design strategies to manage latency, output variance, and graceful error handling at scale ... Research or applied experience with LLM agents, RL (offline/online, RLHF/RLAIF), constrained ...

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Manager Rlhf information

See Edison, NJ salary details

$25.4K

$61.6K

$120.1K

How much do manager rlhf jobs pay per year?

As of Jun 9, 2026, the average yearly pay for manager rlhf in Edison, NJ is $61,623.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,500.00 and $70,900.00 per year, depending on experience, location, and employer.
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Tech Lead Manager- MLRE, ML Systems

Tech Lead Manager- MLRE, ML Systems

Scale AI

Manhattan, NY • On-site

Full-time

Posted 19 days ago


Job description

Job Summary:
Scale AI is a company focused on developing reliable AI systems for critical decisions. They are seeking a Tech Lead Manager for their ML Systems team to build and optimize a training and inference framework that supports machine learning research and development.
Responsibilities:
• Build, profile and optimize our training and inference framework.
• Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
• Research and integrate state-of-the-art technologies to optimize our ML system.
Qualifications:
Required:
• Passionate about system optimization
• Experience with multi-node LLM training and inference
• Experience with developing large-scale distributed ML systems
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
• Strong written and verbal communication skills to operate in a cross functional team environment.
Preferred:
• Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.