Staff AI Engineer
Location
Brazil
Posted
4 days ago
Salary
0
Seniority
Lead
Job Description
Staff AI Engineer
Blip
• Lead and execute the end-to-end lifecycle of language models and AI solutions (APIs, MCPs, Agents) at Blip. • Evaluate and orchestrate transitions between calls to commercial model APIs and internally distilled models deployed in a VPC, aiming for maximum quality, technological autonomy, and cost/latency efficiency. • Design and run rigorous experiments to test new architectures, quantization techniques, and modeling strategies under technical uncertainty. • Build and manage automated large-scale data cleaning and curation pipelines, and orchestrate and monitor inference workloads in cloud environments. • Work closely with product and business teams to ensure AI initiatives align with Blip's strategic objectives.
Job Requirements
- Academic background: Systems Engineering, Computer Science, Computer Engineering, Artificial Intelligence, or related fields.
- Hands-on experience building Teacher–Student architectures, PEFT techniques (LoRA, QLoRA), and adapting/specializing open models for new capabilities.
- Technical ability to compare and integrate proprietary model APIs as well as deploy and customize open models, knowing when to transition between them based on maturity and use-case requirements.
- Experience in high-performance serving of language models and quantization techniques.
- Ability to extract, process, and sanitize large volumes of data, generate high-fidelity synthetic data, and curate training/validation datasets.
- Practical experience with cloud environments and Big Data tools for engineering, analysis, and curation of large-scale datasets, as well as orchestration of microservices and scalable inference engines in production.
- Skill in building Golden Datasets, strict LLM-as-a-Judge frameworks, empirical evaluation and alignment/quality metrics in addition to traditional NLP evaluation metrics.
- Proficiency in Python, PyTorch, efficient GPU utilization, and scalable API and microservice architectures.
- Ability to operate in ambiguous scenarios, rapidly formulate and test hypotheses, discard infeasible approaches, and focus on efforts that deliver real business value.
- Ability to connect R&D advances directly to product needs, turning papers and proofs of concept into productionized capabilities.
- Ability to stay up to date with and maintain relevant knowledge amid the fast-changing LLM and generative AI market.
- Ability to make data-driven decisions balancing Quality vs. Latency vs. Compute Cost vs. Privacy.
- Ability to act as a technical reference within the AI Directorate, mentoring engineers and bridging research vision with business strategy.
- Ability to translate complex Deep Learning concepts, research hypotheses, and infrastructure optimizations into clear ROI and strategic arguments for leadership.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
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