Staff AI Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Oversee and implement the complete lifecycle of language models and AI solutions (APIs, MCPs, Agents) at Blip.

• Assess and manage transitions between calls to commercial model APIs and internally refined models deployed in a VPC, aiming for optimal quality, technological independence, and cost/latency effectiveness.

• Design and conduct thorough experiments to evaluate new architectures, quantization methods, and modeling strategies amidst technical uncertainties.

• Develop and supervise automated large-scale data cleaning and curation pipelines, as well as orchestrate and monitor inference workloads in cloud settings.

• Collaborate closely with product and business teams to ensure that AI initiatives are in line with Blip's strategic goals.

⛳️ Requirements

• Educational background in Systems Engineering, Computer Science, Computer Engineering, Artificial Intelligence, or related disciplines.

• Practical experience in building Teacher–Student architectures, PEFT techniques (LoRA, QLoRA), and adapting/specializing open models for enhanced capabilities.

• Technical expertise to compare and incorporate proprietary model APIs as well as deploy and customize open models, determining the appropriate transitions based on maturity and use-case needs.

• Experience in high-performance serving of language models and application of quantization methods.

• Proficient in extracting, processing, and cleansing large datasets, generating high-fidelity synthetic data, and curating training/validation datasets.

• Hands-on experience with cloud environments and Big Data tools for the engineering, analysis, and curation of extensive datasets, along with orchestrating microservices and scalable inference engines in production.

• Competence in creating Golden Datasets, implementing strict LLM-as-a-Judge frameworks, and utilizing empirical evaluation and alignment/quality metrics in addition to standard NLP evaluation metrics.

• Proficiency in Python, PyTorch, optimizing GPU usage, and designing scalable API and microservice architectures.

• Ability to navigate ambiguous situations, quickly formulate and evaluate hypotheses, discard impractical approaches, and concentrate on efforts that yield tangible business value.

• Capability to connect R&D advancements directly to product demands, transforming research papers and proofs of concept into production-ready capabilities.

• Commitment to staying informed and maintaining relevant knowledge in the rapidly evolving LLM and generative AI landscape.

• Skill in making data-driven decisions that balance Quality, Latency, Compute Cost, and Privacy.

• Capacity to serve as a technical resource within the AI Directorate, mentoring engineers and aligning research vision with business strategy.

• Proficiency in translating intricate 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