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Back-End Developer with AI Experience

External
getwingapp logoGetwingapp · Manila, Philippines
Full-timeRemote5mo ago
AWSAzureComputer VisionDjangoDockerETL
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Responsibilities

  • Design, develop, and maintain scalable back-end systems, APIs, and
  • microservices.
  • Integrate AI/ML models (NLP, computer vision, recommendation systems, etc.)
  • into production applications.
  • Collaborate with front-end developers, AI/ML engineers, and data scientists to
  • deliver end-to-end AI-powered features.
  • Optimize databases, APIs, and system performance to handle large-scale
  • data processing and real-time AI inference.
  • Implement secure authentication, authorization, and data protection
  • practices.
  • Build and manage data pipelines to support training, testing, and deployment
  • of AI models.
  • Monitor, debug, and improve system reliability and AI feature performance.
  • Stay current with emerging technologies in AI/ML, cloud services, and back-end frameworks.

Requirements

  • -Bachelor's degree in Computer Science, Software Engineering, or a related
  • field (or equivalent experience).
  • Proven experience as a Back-End Developer (3+ years).
  • -Strong proficiency in at least one back-end language/framework (Node.js,
  • Python/Django, Java/Spring Boot, or Go).
  • -Hands-on experience integrating AI/ML APIs or deploying machine learning
  • models into production (e.g., TensorFlow, PyTorch, Hugging Face, OpenAI APIs).
  • Experience with relational and non-relational databases (MySQL, PostgreSQL,
  • MongoDB, etc.).
  • Familiarity with RESTful APIs, GraphQL, and microservices architecture.
  • Knowledge of cloud services (AWS, GCP, or Azure) for deploying AI-enabled
  • applications.
  • Strong debugging, performance tuning, and problem-solving skills.
  • Preferred Skills:
  • Experience with MLOps tools (Kubeflow, MLflow, or Vertex AI).
  • Knowledge of containerization and orchestration (Docker, Kubernetes).
  • Background in data engineering (ETL pipelines, real-time data streaming).
  • Familiarity with serverless computing and edge AI deployment.
  • -Experience with security best practices in AI applications (data privacy, model
  • security).
  • Technical Requirements:
  • USB Headset with Noise Cancellation feature
  • Working Webcam
  • Computer with at least 1.8 GHz processor and at least 4GB RAM
  • Main Internet Service Speed: at least 25 Mbps cable connection
  • Backup Internet Service Speed: at least 10 Mbps

Benefits

Health Insurance (HMO)Performance IncentivesJob Security and StabilityPaid TrainingInclusive CultureUpskilling Opportunities100% Work-From-HomeExceptionally Supportive TeamOpportunities for Career GrowthFun Work EnvironmentHoliday & Overtime PaySchedule: US work hours (20-40 hours per week)Location: This is a remote jobPlease note:Only qualified candidates will be invited to take the assessment & scheduled for an interview.We have other vacancies that might interest your friends & colleagues. They can check us out at our Jobs Website.You may also refer your friends using our Affiliate Marketing Program and earn up to $30 if your referral is hired.

Additional Information

Please whitelist the domains "lever.co" and "hire.lever.co" with your email provider to make sure you get our emails. Disclaimer: This is a generic job description for the position stated below. Actual tasks and tools will be discussed further when you reach the final interview stage. Please ensure you apply for the right job based on your location and experience. We prioritize people who can do this successfully! Back-End Developer with AI Experience Wing is on the exciting mission of redefining the future of work for companies worldwide! We are looking to be the one-stop shop for companies that are looking to build world-class teams & place their operations on autopilot. We are looking for a Back-End Developer with AI experience to design, build, and maintain server-side applications and services that power AI-driven solutions. The ideal candidate has strong expertise in back-end technologies, database management, and cloud infrastructure, combined with hands-on experience integrating and deploying AI/ML models and APIs.


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