Data Scientist

5+ years of industry experience in Data Science, Machine Learning Research, or a closely related field, with a strong emphasis on deep learning.

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or another quantitative discipline.

Expert-level Python skills with deep proficiency in PyTorch or JAX.

Demonstrated experience training and deploying large-scale models (e.g., LLMs, diffusion models) in distributed production environments.

Deep understanding of distributed training paradigms, including data parallelism, pipeline parallelism, and tensor parallelism.

Strong mathematical foundation in linear algebra, calculus, and optimization, particularly as applied to neural network training and convergence.

Experience working with data-at-scale tooling, such as Spark, Ray, or high-throughput data loading frameworks.

PhD in a relevant field, with publications at top-tier conferences (e.g., NeurIPS, ICML, ICLR).

Hands-on experience with Mixture-of-Experts (MoE) architectures, including routing and load-balancing challenges.

Familiarity with RLHF workflows, including PPO and DPO fine-tuning pipelines.

Knowledge of model quantization techniques (e.g., FP8, INT8, AWQ) and their impact on training stability and inference performance.

Contributions to open-source ML libraries or involvement in high-profile LLM releases.

Sciforium is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.