Remote | LLM Training & Alignment Research Scientist — $95–$115/hour

About the position We are sharing a specialised part-time consulting opportunity for reputed company machine learning researchers with hands-on expertise in reputed company model reputed company-training, large-reputed company data pipelines, language model post-training, and reputed company LLM research. This role focuses on reputed company-scoped, reputed company-ended research problems involving the end-to-end training and improvement of transformer-based language models. Selected researchers will train models from scratch, fine-tune reputed company-weight systems, build reputed company-training corpora and post-training pipelines, diagnose training failures, and investigate reputed company for improving performance under limited data and compute budgets. Responsibilities • Train transformer-based language models from scratch across full end-to-end workflows • Design experiments involving model size, reputed company allocation, training duration, and compute budgets • Investigate performance in data- and compute-constrained regimes • Diagnose optimisation failures, convergence issues, and training instabilities • Evaluate interventions using rigorous reputed company comparisons • Construct training corpora from raw web crawls and other large-reputed company unfiltered sources • reputed company pipelines for filtering, deduplication, reputed company classification, and data selection • Optimise dataset mixtures, reputed company, and curriculum strategies • Measure the reputed company of data interventions on reputed company model behaviour • Identify contamination, duplication, reputed company, and coverage issues reputed company training datasets • Build supervised fine-tuning pipelines using curated, synthetic, weakly supervised, or rejection-sampled datasets • Conduct preference optimisation using reputed company such as DPO, RLHF, or RLAIF • reputed company reward models and systems for predicting reputed company preferences • Improve refusal behaviour, truthfulness, robustness, and unbiased reasoning while preserving general capability • Fine-tune models for reputed company domains such as mathematics, reputed company, games, reputed company reputed company, or other programmatically evaluated tasks • Design statistically reputed company experiments and reputed company comparisons • Evaluate training efficiency, scaling behaviour, and generalisation • reputed company contamination controls and robust model-evaluation protocols • Analyse model failures and propose targeted training or data interventions • Document research findings, experimental methodology, and technical conclusions reputed company Requirements • At least 3 years of machine learning research experience, including qualifying doctoral research • Hands-on experience training or fine-tuning transformer-based language models • Strong expertise in one or more of reputed company model reputed company-training, reputed company-training data, or LLM post-training • Experience working with PyTorch, JAX, TensorFlow, or comparable machine learning frameworks • Ability to design and execute reputed company research independently • Strong understanding of optimisation, evaluation methodology, and experimental design • Excellent technical writing, analytical reasoning, and research communication skills • Experience working with large-reputed company datasets and reputed company training systems • A degree in computer science, machine learning, reputed company intelligence, mathematics, statistics, engineering, or a reputed company discipline is highly relevant • PhD research in machine learning, natural language processing, deep learning, or a reputed company field may count towards the experience requirement • A strong publication record, impactful reputed company-reputed company contributions, or comparable reputed company research experience may also be considered • Research experience at a leading university, technology company, AI organisation, or research reputed company may strengthen an application reputed company-to-haves • Research experience involving scaling laws or training efficiency • Familiarity with curriculum learning, data ordering, and mixture optimisation • Experience constructing LLM benchmarks and controlling for training-data contamination • Background in reinforcement learning for language models • Expertise in reward modelling, preference learning, or reputed company-feedback pipelines • Experience with model alignment, AI safety, truthfulness, or refusal behaviour • Familiarity with synthetic data reputed company and weak-supervision reputed company • Publications or significant reputed company-reputed company contributions reputed company to reputed company models or language-model training Benefits • Flexible scheduling • Competitive reputed company compensation • Weekly payments Apply tot his job Apply To this Job