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Blend360
Blend360
501 – 1.000 Angajați
Sponsor pentru viza H1BAsistență medicalăCălătoriiOspitalitate
Blend360 este o companie de servicii profesionale care ajută companiile din Fortune 1000 și alte întreprinderi mari să abordeze provocări complexe de afaceri prin inteligență artificială, analiză de date și soluții bazate pe date. Activitatea sa acoperă inteligența de afaceri, ingineria datelor, știința datelor, operațiunile de învățare automată și guvernanța datelor, reunind echipe de specialiști și capacități de inteligență artificială pentru a sprijini organizații din domeniul sănătății, al serviciilor financiare, al energiei, al comerțului cu amănuntul, al tehnologiei, al mass-mediei și telecomunicațiilor, precum și al călătoriilor și ospitalității. Activitatea Blend360 a fost recunoscută prin distincții precum «Soluția anului pentru facilitarea inteligenței artificiale» și includerea în clasamentul «Cei mai buni furnizori de servicii de inteligență artificială generativă din 2024».
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Locurile de muncă ale companiei

Lead AI Engineer – Argentina Remote

Lead the delivery of production-grade RAG, agentic, and LLM solutions at Blend360. Manage AI engineering teams while shaping evaluation, MLOps, and scalable infrastructure.

ARArgentinaRemoteNormă întreagăSeniorLimbă Obligatorie: englezăInginer AIInginer de învățare automată
AWSAzureCloudGoogle Cloud PlatformMicroserviciiPython

Descriere

  • Own end-to-end project delivery, including governance, stakeholder communication, and accountability for results
  • Build and develop a high-performing AI engineering team
  • Set technical standards and promote a pragmatic, quality-focused engineering culture
  • Lead proposals and new-business efforts by assessing technical feasibility and explaining client risks and tradeoffs
  • Set practical boundaries and expectations for AI capabilities
  • Perform technical reviews and assess solution architectures
  • Direct the design and delivery of production-ready RAG systems, agentic frameworks, and LLM applications
  • Lead sophisticated prompt-engineering work spanning instruction design, few-shot examples, structured outputs, and tool or agent prompts
  • Assess feasibility across prompting, RAG, fine-tuning, and traditional machine learning
  • Coach engineers in AI system design and production deployment
  • Create evaluation frameworks using LLM-as-a-judge, recall@k, precision@k, and go/no-go criteria
  • Run controlled experiments involving prompts, retrievers, chunking approaches, and models
  • Implement methods for detecting and classifying model failures
  • Define reliability standards for AI systems in production
  • Develop scalable inference infrastructure and CI/CD pipelines
  • Automate MLOps and LLMOps processes for tracking, versioning, deployment, monitoring, and retraining
  • Design APIs, microservices, and orchestration layers optimised for latency, cost, and reliability
  • Make infrastructure decisions that balance technical quality with business efficiency

Cerințe

  • At least five years of experience building and deploying AI solutions in production
  • Expert-level Python skills
  • Strong working practices with Git
  • Experience versioning and deploying machine learning and large language model systems
  • Solid experience with AWS, Azure, or GCP, with Azure preferred
  • Knowledge of containerisation and orchestration
  • Hands-on RAG experience with chunking, embeddings, retrieval, reranking, and evaluation
  • Demonstrated MLOps or LLMOps experience with MLflow, Weights & Biases, or comparable tools
  • Practical expertise designing evaluations, including metrics, dataset curation, and structured experimentation
  • Experience developing event-driven architectures, APIs, and microservices
  • Ability to communicate clearly with engineering teams and senior stakeholders
  • Strong hiring and team-building judgement, supported by proven mentoring experience
  • Advanced English required for communication with global teams and client leadership
  • At least two years of direct team leadership or technical management experience

Beneficii

  • Certification opportunities in AWS, Databricks, and Snowflake
  • Access to AI-focused learning paths
  • Role-specific study plans, courses, and additional certification opportunities
  • Access to Udemy Business
  • English-language lessons
  • Travel opportunities for industry conferences and client meetings
  • Career development planning and mentorship programmes
  • Special-day rewards for birthdays, work anniversaries, and other personal milestones
  • Company-provided equipment
  • Flexible working options
  • Additional benefits may differ by location within LATAM

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