Full-Time AI Engineer

• Design, implement, and optimize AI/ML models for real-world applications.
• Integrate LLMs, generative AI, and ML models into production systems.
• Collaborate with backend/frontend teams to deliver end-to-end AI-powered 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 with GitHub Actions, Docker, and Kubernetes.
• Ensure AI systems follow best practices for security, performance, and responsible use.
• Mentor engineers and share AI/ML knowledge across the team.

• Software Development: Strong foundation in Python (AI/ML stack) plus production development experience in Java, Spring Boot, or similar.
• AI/ML Expertise: Practical experience with frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face.
• AI APIs & Integrations: Hands-on experience with OpenAI, AWS AI, Vertex AI, or similar platforms.
• Cloud Infrastructure: Skilled in deploying and managing AI workloads on AWS (SageMaker, EC2, S3, RDS, Lambda).
• Data Engineering: Experience working with SQL/NoSQL databases, pipelines, and preprocessing for model training.
• MLOps & CI/CD: Proficiency with GitHub, GitHub Actions, Docker, Kubernetes; experience automating model training and deployment.
• Soft Skills: Strong collaboration, excellent communication, resourceful problem-solver, accountability, adaptability.

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