Backend Engineer with ML focus (US Based)
Back-End Developer, AI Developer
Required skills: SQL, Python
Nice to have skills: Java, Go, scikit-learn, Redis, PyTorch, Kafka
This enterprise software company provides an AI platform designed to automate complex operations such as demand forecasting and supply chain optimization. The platform bridges the gap between experimental pilots and production-ready workflows, enabling organizations in global industries to deploy scalable AI solutions. By focusing on governed intelligence and data integration, the company helps businesses achieve operational efficiency through an interface for building and managing production-grade AI applications at scale.
About the Role
As a software engineer, you will design and own production systems end-to-end, focusing on the infrastructure required to operationalize machine learning models. You will be responsible for building the scalable APIs, microservices, and data pipelines that support reliable AI applications. Rather than focusing on model training, your impact lies in shipping the robust systems that surround these models, ensuring high performance, fault tolerance, and observability at scale. You will act as the primary bridge between core backend engineering and machine learning deployment.
What You’ll Do
- Design and maintain scalable APIs and microservices to support high-throughput production environments.
- Build robust data pipelines for model ingestion and processing using SQL and NoSQL databases.
- Deploy machine learning models via specialized inference frameworks and serving patterns like batching and async inference.
- Implement observability across the stack, including comprehensive logging, metrics, and alerting systems.
- Architect distributed systems focusing on low latency, fault tolerance, and message queuing.
- Triage and debug machine learning models in production to ensure consistent performance and reliability.
- Manage embedding pipelines and integrate vector search capabilities to enhance application intelligence.
What You Bring
- Extensive experience building and maintaining production-grade backend systems in languages such as Python, Go, or Java.
- Strong understanding of system design principles, including distributed systems and data consistency.
- Technical proficiency with SQL and NoSQL databases, caching layers, and message brokers like Kafka or Redis.
- Proven experience shipping to production with built-in observability and monitoring.
- Practical knowledge of machine learning libraries such as PyTorch, scikit-learn, or HuggingFace for model integration and debugging.
- Based in the US with authorization to work in the USA, no visas or sponsorships.
Nice to Haves
- Experience with vector search engines and embedding pipelines.
- Knowledge of advanced model serving patterns and asynchronous inference.
- Prior experience in manufacturing, retail, or finance sectors.
About your mission
Support enterprise customers in adopting and scaling AI solutions by partnering closely to translate business needs into practical, high-impact technical implementations. Work collaboratively to design, develop, and deploy machine learning and AI applications using the platform, ensuring solutions align with customer objectives and deliver measurable value. Contribute to end-to-end AI initiatives - from problem definition through deployment, while maintaining a strong focus on scalability, reliability, and real-world impact.
About the client
We are an enterprise AI platform helping organizations unlock value from their data by combining autonomous AI agents with human expertise. Our platform enables companies to build and deploy enterprise-grade AI solutions faster and more cost-effectively than traditional approaches, delivering measurable outcomes across industries such as manufacturing, retail, financial services, and infrastructure.
Our mission is to make advanced AI accessible to every organization - not just teams with large data science departments or deep technical resources.
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