Vaga de parceiro

Ai Platform Engineer - Goiás / GO

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Detalhes da Vaga

  • Escolaridade Não Informado
  • Segmento Não Informado
  • Salário Não Informado
  • Área de AtuaçãoDiversos / Outros

O que você irá fazer

  • This role will focus on enabling teams to work more efficiently by implementing AI-powered solutions, best practices, and MLOps strategies.
  • The ideal candidate has proven experience working with engineering and technology companies to drive AI adoption across engineering, sales, and marketing , ensuring AI initiatives deliver measurable impact and efficiency gains.
  • This role requires a combination of technical expertise in AI / ML infrastructure, strategic thinking to identify high-value AI opportunities, and cross-functional collaboration to help teams seamlessly integrate AI into their workflows.
  • The AI Platform Engineer will play a key role in automating processes, optimizing team operations, and ensuring AI solutions align with business goals .
  • Key Responsibilities : AI Tooling & Infrastructure : Design, implement, and scale AI / ML tooling that improves team efficiency, streamlines workflows, and enhances automation.
  • MLOps Best Practices : Help engineering teams implement effective MLOps processes, including model deployment, monitoring, and lifecycle management.
  • Cross-Team Collaboration : Work closely with software engineering, data science, and operations teams to integrate AI capabilities into their workflows.
  • AI Adoption & Enablement : Drive organization-wide adoption of AI by identifying key pain points, providing education, and ensuring seamless integration of AI solutions.
  • Automation & Efficiency : Develop AI-powered automation solutions to reduce manual work, improve productivity, and optimize team operations.
  • Scalability & Performance : Ensure AI infrastructure and workflows are scalable, resilient, and efficient to support company-wide initiatives.
  • Security & Compliance : Implement AI governance, security best practices, and compliance measures to align with organizational and regulatory standards.
  • Monitoring & Evaluation : Establish metrics and feedback loops to measure the impact of AI tooling on team efficiencies and continuously improve processes.
  • Qualifications : Technical Expertise : 5+ years of experience in software engineering, MLOps, or AI infrastructure roles.
  • Strong programming skills in Python, Go, or another relevant language.
  • Experience with AI / ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
  • Proficiency in cloud platforms (AWS, GCP, or Azure) and AI / ML services.
  • Hands-on experience with containerization (Docker, Kubernetes) and orchestration tools.
  • Familiarity with AI observability, monitoring, and governance tools.
  • Strong understanding of CI / CD pipelines, infrastructure as code (Terraform, Pulumi), and automation best practices.
  • MLOps & AI Operations : Experience implementing MLOps pipelines for model training, deployment, and monitoring.
  • Familiarity with vector databases, feature stores, and AI-powered search.
  • Knowledge of distributed computing and optimizing AI workloads for efficiency.
  • Soft Skills & Adoption Focus : Excellent problem-solving and analytical skills to identify high-impact AI solutions.
  • Ability to work cross-functionally and communicate effectively with non-technical stakeholders.
  • Strong ability to drive change, facilitate AI adoption, and enable teams to succeed with AI-driven processes.
  • Passion for AI automation, operational efficiency, and developer experience.
  • Success Metrics for This Role : Adoption Rate : Increase in AI tooling adoption across engineering, sales, and marketing teams.
  • Efficiency Gains : Measurable reductions in manual effort and time spent on repetitive tasks.
  • MLOps Maturity : Improved model deployment velocity and reliability through MLOps best practices.
  • Developer Productivity : Reduction in friction for AI-enabled engineering teams.
  • Feedback & Iteration : Continuous improvement based on team feedback and usage metrics.
  • Please answer the questions in detail in the given link to move forward with the screening process.
  • Answer the questions #J-18808-Ljbffr

Informações Adicionais

  • Quantidade de Vagas 1
  • Jornada Não Informado
 

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