Backend Engineer with ML focus

About the role

We are looking for a Backend Engineer who will own the end‑to‑end production systems that operationalize machine‑learning models. Your work will focus on building the infrastructure, APIs, and data pipelines that enable reliable, high‑performance AI applications at scale.

Key responsibilities

• Design, develop, and maintain scalable APIs and microservices for high‑throughput environments.
• Build robust data pipelines for model ingestion and processing using SQL and NoSQL databases.
• Deploy machine‑learning models with specialized inference frameworks, supporting batching and asynchronous inference.
• Implement full‑stack observability, including logging, metrics, and alerting.
• Architect distributed systems with low latency, fault tolerance, and message‑queuing capabilities.
• Triage and debug production ML models to ensure consistent performance.
• Manage embedding pipelines and integrate vector‑search capabilities to enhance application intelligence.

Required profile

• Extensive experience building production‑grade backend systems in Python, Go, or Java.
• Strong grasp of system design, distributed architectures, and data consistency.
• Proficiency with SQL and NoSQL databases, caching layers, and message brokers such as Kafka or Redis.
• Proven track record of shipping services with built‑in observability and monitoring.
• Practical knowledge of ML libraries like PyTorch, scikit‑learn, or HuggingFace for model integration and debugging.

Required skills

• Python
• Go
• Java
• SQL
• NoSQL
• Kafka
• Redis
• APIs
• Microservices
• Data pipelines
• Observability (logging, metrics, alerting)
• Distributed systems
• Message queuing
• PyTorch
• scikit‑learn
• HuggingFace
• Vector search
• Embedding pipelines