We are looking for a high-impact AI/MLOps Engineer to join our engineering team. You won’t just be “playing with prompts”; you will be responsible for the entire lifecycle of our machine learning models. Your mission is to build robust, automated pipelines that transition AI from experimental notebooks into high-performance production environments.

Key Responsibilities

• Model Deployment & Scaling: Design and implement CI/CD pipelines specifically for ML (MLOps), ensuring seamless deployment of LLMs, computer vision, or predictive models.

• Infrastructure Management: Architect and maintain scalable infrastructure (Kubernetes, Docker, Cloud-native tools) to support model training and real-time inference.

• Data Engineering: Collaborate with data teams to build automated data pipelines (ETL/ELT) ensuring high-quality data reaches our models.

• Monitoring & Observability: Implement rigorous monitoring for model drift, latency, and system health to ensure our AI remains reliable and accurate.

• Collaboration: Act as the “glue” between Data Scientists and Backend Engineers, translating complex research into production-ready code.

Technical Stack (Required)

• Languages: Expert-level Python (familiarity with Rust or Go is a plus).

• ML Frameworks: Deep experience with PyTorch, TensorFlow, or Jax.

• Cloud & Infrastructure: Hands-on experience with AWS/GCP/Azure, Kubernetes (K8s), and Terraform/Pulumi.

• MLOps Tools: Experience with tools like Kubeflow, MLflow, Weights & Biases, or DVC.

• Databases: Proficiency with SQL, NoSQL, and Vector Databases (Pinecone, Milvus, or Weaviate) for RAG-based architectures.

Qualifications

• 3+ years of experience in a DevOps, SRE, or Machine Learning role.

• Strong understanding of the LLM ecosystem (LangChain, LlamaIndex, fine-tuning strategies).

• A “production-first” mindset: You care about unit tests, documentation, and system uptime as much as model accuracy.

• Degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).