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Staff AI Engineer

9 hours, 15 minutes ago
Brazil
Lead
AI Engineer
Software Development
Deep Learning GCP Hugging Face LLM Machine Learning Microservices NLP Python PyTorch Vertex AI
Apply Now
Blip

Blip

Blip is an automated communications platform that assists in digital customer interactions. As an official WhatsApp provider and partner of Meta, Blip revolutionizes brand communication with integrated chatbots and smart contacts. Explore a single tool...

Internet Software & Services
1-10
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Description

  • Design, train, validate, deploy, and evolve custom language models and adapters for the product ecosystem.
  • Lead applied research and experimentation across model architectures, quantization techniques, and modeling strategies under technical uncertainty.
  • Evaluate and orchestrate the transition between commercial model APIs and internal distilled models to balance quality, autonomy, cost, latency, and privacy.
  • Build and manage automated pipelines for large-scale data cleaning, curation, and dataset preparation for training and validation.
  • Handle data extraction, treatment, sanitization, and synthetic data generation for machine learning use cases.
  • Operate, monitor, and continuously improve inference workloads and scalable model-serving infrastructure in cloud environments.
  • Work closely with product and business teams to align AI initiatives with Blip’s strategic goals.
  • Define evaluation frameworks, including golden datasets and strict LLM-as-a-Judge methods, to measure alignment and quality.
  • Mentor engineers and act as a technical reference point within the AI organization.

Requirements

  • Degree in Systems Engineering, Computer Science, Computer Engineering, Artificial Intelligence, or a related field.
  • Strong practical experience with knowledge distillation and fine-tuning, including teacher-student architectures and PEFT methods such as LoRA and QLoRA.
  • Ability to compare, integrate, and transition between proprietary model APIs and open models according to use-case maturity and requirements.
  • Experience with high-performance model serving and inference optimization, including quantization techniques.
  • Hands-on experience in cloud environments and big data tools for data engineering, analysis, and large-scale curation.
  • Experience orchestrating scalable microservices and inference engines in production.
  • Ability to build golden datasets, strict LLM-as-a-Judge frameworks, and empirical evaluation methods beyond traditional NLP metrics.
  • Strong Python and PyTorch skills, with efficient GPU usage and scalable API/microservices architecture experience.
  • Comfort working in ambiguous research settings and rapidly testing hypotheses.
  • Preferred: experience with Google Cloud Platform, especially BigQuery, Google Kubernetes Engine, and Vertex AI / Agent Platform.
  • Preferred: proven experience distilling large-model capabilities into smaller models in production at scale.
  • Preferred: publications, technical articles, or open-source contributions in the ML/LLM ecosystem such as Hugging Face, vLLM, or PyTorch.
  • Preferred: advanced knowledge of GPU optimization, including PagedAttention, Continuous Batching, acceleration kernels, and model compilation.

Interested in this position?

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