Astek
Senior LLM Researcher - Alignment

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Senior LLM Researcher - Alignment
For one of our clients, we are looking for a Senior LLM Researcher - Alignment to help build reliable, safe, and high-performing language models.
In this role, you will design and implement alignment, sanitization, evaluation, and guardrailing pipelines that enable the delivery of trustworthy AI at scale. You will also play a key role in advancing Arabic-focused language model capabilities, including dialectal coverage and culturally relevant safety considerations.
Key Responsibilities
- Own alignment strategies, including:
- Supervised fine-tuning (SFT)
- Preference optimization, such as DPO and RLHF
- Reward modeling
- Rejection sampling
- Constrained decoding
- Design and build end-to-end alignment pipelines covering data curation, training, preference optimization, and evaluation.
- Develop data pipelines for filtering, augmentation, preference-data collection, and quality control.
- Build model sanitization workflows, including:
- PII removal
- Data redaction
- Prompt and response scrubbing
- Harmful-pattern filtering
- Implement runtime guardrails using policy models, classifiers, rule engines, retrieval-based safety checks, and rate controls.
- Establish red-teaming and adversarial testing programs, including incident taxonomies and response playbooks.
- Define and maintain evaluation frameworks covering safety, robustness, task performance, drift, latency, and telemetry.
- Expand Arabic language coverage across dialects, domains, and culturally relevant safety scenarios.
- Partner with product, platform, and engineering teams to move research into production.
- Mentor engineers and researchers while developing internal documentation, playbooks, and best practices.
- Lead major AI initiatives that improve model helpfulness, harmlessness, faithfulness, reliability, and cost efficiency.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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Requirements
- Proven research or industry experience training and aligning large language models.
- Strong hands-on experience with SFT and preference optimization, including RLHF, DPO, or reward modeling.
- Strong machine learning theory and engineering capabilities.
- Demonstrated experience in LLM safety and security, including guardrails, classifiers, adversarial prompting, or PII handling.
- Experience designing evaluation frameworks for model quality, safety, robustness, and reliability.
- Track record of taking research from experimentation through production, supported by clear metrics and documentation.
- Strong programming skills in Python and experience with modern deep learning frameworks, particularly PyTorch.
- Ability to work cross-functionally and communicate complex research clearly.
- Experience mentoring engineers, researchers, or technical teams.


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Nice to Have
- Experience with red-teaming, AI policy design, or compliance in multilingual environments.
- Familiarity with Arabic NLP, including dialectal variation.
- Knowledge of retrieval-augmented generation, constrained decoding, or tool-use agents.
- Experience with inference optimization, quantization, low-latency serving, or observability.
- Familiarity with distributed training environments and large-scale model deployment.
- Experience with systems such as Hugging Face, Slurm, LlamaFactory, NeMo, RLHF/DPO frameworks, vector databases, and policy or guardrail services.
- Experience working with H200 or similar GPU infrastructure.
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