AI Engineer (Generative AI & MLOps) – Job Opportunity

Role Summary: We are seeking a talented AI Engineer with a strong focus on Generative AI and MLOps. In this role, you will build cutting-edge machine learning solutions for global clients, helping to solve real-world problems through innovative technology.

What We’re Looking For

We are seeking a candidate with a strong foundation in the following areas. This is not a checklist of hard requirements, but a guide to the ideal candidate profile.

• 3-5 years of professional experience
• 1-2 years of hands-on experience in AI/ML
• Proficiency in Python
• Experience with PyTorch or TensorFlow
• Familiarity with frameworks like Hugging Face, LangChain, etc.
• Hands-on experience with LLMs and Generative AI
• Knowledge of Cloud MLOps on platforms like AWS, GCP, or Azure
• Experience with containerization using Docker & Kubernetes

What You’ll Do: A Day in the Life

As an AI Engineer, you will be responsible for a wide range of tasks that span the full machine learning lifecycle.

• Design & Develop Models: Create robust AI/ML models and algorithms with a focus on modern deep learning architectures.
• Build MLOps Pipelines: Build and maintain scalable pipelines for model training, versioning, and deployment using tools like MLflow.
• Leverage Generative AI: Work on exciting projects involving Generative AI, computer vision, and advanced NLP techniques like RAG.
• Collaborate & Integrate: Partner with product and engineering teams to integrate AI-driven APIs and microservices into our products.
• Monitor & Improve: Maintain model performance via CI/CD, monitoring for model and data drift to ensure reliability.
• Stay Ahead of the Curve: Continuously research and implement the latest AI advancements and industry best practices.

Our Tech Stack

Our team uses a modern tech stack focused on building and deploying AI at scale. The following represents the key areas of expertise we are looking for:

• Python
• Deep Learning (PyTorch/TF)
• LLM Frameworks (Hugging Face, LangChain)
• MLOps (MLflow)
• Cloud Platforms (AWS, GCP, Azure) and specific services like AWS SageMaker or GCP Vertex AI
• Containerization (Docker, Kubernetes)
• Version Control (Git)
• API Development (FastAPI, Flask)
• Data Handling and Databases (SQL, Spark)

What We Offer

• Flexible Remote Work: Enjoy the freedom and flexibility of a remote-first work environment.
• Dynamic Team: Collaborate with an experienced, passionate, and supportive team.
• Career Growth: Access opportunities for continuous learning and professional development.

Ready to make an impact with AI?