ML Data Engineer (AI)

Location: Hybrid in San Francisco or Boston; other locations may be considered

Company

hirify.global, spun out of MIT CSAIL, develops general-purpose AI systems optimized for low latency, low memory usage, privacy, and reliability across data center and on-device hardware.

What you will do

• Build and maintain large-scale data processing, filtering, and selection pipelines.
• Create datasets and pipelines for pre-training, mid-training, supervised fine-tuning, and preference optimization.
• Design synthetic data generation systems using LLMs, structured prompting, and domain-specific generators.
• Run evaluations and ablation studies to measure the impact of datasets on model performance.
• Monitor public datasets across text, vision, and audio domains.
• Collaborate with pre-training, vision, audio, and multimodal teams on modality-specific data needs.

Requirements

• Strong Python skills and the ability to translate complex problems into clean, working code.
• Solid machine learning fundamentals, including training, evaluating, and iterating on models; PyTorch is preferred.
• Ability to learn new technical domains quickly and work independently in ambiguous environments.
• 3+ years of relevant experience with an M.S., 1+ year with a Ph.D., or 5+ years with a B.S.

Nice to have

• Experience with synthetic data generation, data curation, or machine learning evaluation.
• Experience with LLMs, VLMs, computer vision, or audio data pipelines.
• Open-source contributions or publications at NeurIPS, ICML, ICLR, or CVPR.

Culture & Benefits

• Own critical data pipelines end-to-end for foundation-model modalities.
• Work on systems whose data quality directly affects model performance at scale.
• Competitive base salary with equity in a unicorn-stage company.
• 100% coverage of medical, dental, and vision premiums for employees and dependents.
• 401(k) matching of up to 4% of base pay.
• Unlimited paid time off and company-wide Refill Days.