Vinmar International

AI Engineer

Vinmar International

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

AWSCloudDockerEC2JavaKubernetesNoSQLPythonPyTorchScikit-LearnSpringSpring BootSpringBootSQLTensorflow

About the role

  • Build and deploy AI/ML solutions powering customer-facing products and internal platforms
  • Design, implement, and optimize AI/ML models for real-world applications
  • Integrate LLMs, generative AI, and ML models into production systems and user-facing applications
  • Write production-grade code and work across the stack with backend/frontend teams to deliver end-to-end AI features
  • Own the AI/ML lifecycle: data collection, preprocessing, model training, evaluation, deployment, and monitoring
  • Build scalable cloud-based AI solutions using AWS SageMaker, Lambda, EC2, and other managed services
  • Develop CI/CD pipelines for AI workloads using GitHub Actions, Docker, and Kubernetes
  • Ensure AI systems follow best practices for security, performance, and responsible use (bias, fairness, explainability)
  • Mentor engineers, share AI/ML knowledge, and help define architecture and practices alongside senior engineers
  • Collaborate across teams to shape how AI is applied within products and influence technical direction

Requirements

  • Strong foundation in Python (AI/ML stack) plus production development experience in Java, Spring Boot, or similar
  • Practical experience with frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face
  • Hands-on experience with OpenAI, AWS AI, Vertex AI, or similar platforms
  • Skilled in deploying and managing AI workloads on AWS (SageMaker, EC2, S3, RDS, Lambda)
  • Experience working with SQL/NoSQL databases, pipelines, and preprocessing for model training
  • Proficiency with GitHub, GitHub Actions, Docker, Kubernetes; experience automating model training and deployment
  • Strong collaboration across product, data, and engineering teams
  • Excellent communicator who can translate AI/ML concepts into actionable engineering tasks
  • Resourceful problem-solver with a “figure it out” mindset and ability to work independently
  • Demonstrates accountability, ownership, and a commitment to high-quality engineering
  • Adaptable and proactive learner, staying ahead of emerging AI trends
  • Familiar with Agile/Kanban development practices
  • Preferred: Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related field
  • Preferred: Hands-on experience with LLMs, embeddings, RAG (retrieval-augmented generation), and vector databases (Pinecone, Weaviate, FAISS)
  • Preferred: Prior experience bringing AI systems into production at scale
  • Preferred: Knowledge of responsible AI practices: fairness, bias mitigation, explainability