We are looking for a Senior Backend Engineer to join our AI/ML team. In this role, you’ll work closely with data scientists to transform cutting-edge machine learning models into scalable, production-ready services. You will take ownership of designing, building, and maintaining the backend systems that power our AI-driven features.

This is a key position that bridges the gap between data science and production engineering, ensuring high performance, reliability, and maintainability of our ML-powered products.

Responsibilities:

• Collaborate with data scientists to understand modeling outputs and convert them into deployable services.
• Design and develop robust, scalable backend systems and microservices to support AI use cases.
• Own the deployment and monitoring of ML models in production (with CI/CD, logging, observability).
• Implement data processing pipelines in support of model training and inference.
• Ensure software adheres to best practices in architecture, testing, and documentation.
• Optimize model inference for latency, throughput, and resource efficiency.
• Contribute to design decisions and technical strategy alongside AI and infrastructure leads.

Requirements:

• 5+ years of experience as a backend/software engineer, preferably in Python, Go, or Java.
• Strong experience with designing APIs, building microservices, and integrating third-party services.
• Familiarity with ML workflows: model serving, feature extraction, and batch vs real-time inference.
• strong architectural/design skills, including working with message queues like Kafka, relational and NoSQL databases, and distributed systems.
• Experience deploying services in containerized environments (e.g., Docker, Kubernetes).
• Proficient with cloud-native tools or on-prem equivalents (e.g., logging, tracing, metrics).
• Knowledge of data processing frameworks (e.g., Pandas, Spark, Airflow) is a plus.
• Comfortable reading and working with Python-based ML code (scikit-learn, TensorFlow, PyTorch, etc.).
• Strong ownership mindset and a collaborative attitude.

Nice to Have

• Experience with model versioning and ML serving frameworks (e.g., MLflow, Seldon, Triton).
• Understanding of data privacy/security implications in model and data pipelines.
• Experience working in cross-functional teams with data scientists and product owners.