We are looking for a highly motivated backend software engineer specializing in creating high-scale, distributed backend systems.
You will design and implement ML/AI infrastructure components (model‑serving APIs, inference pipelines, feature stores).
Collaborate closely with data scientists and data engineers to productionize models and automate retraining workflows.
You must demonstrate strong software engineering skills, excellent interpersonal communication, extreme ownership, and the ability to accept and give meaningful technical feedback.
You will be responsible for designing architecture, writing correct, robust code, maintaining and improving existing functionality, and shipping new features.
You will work as part of a Scrum-Agile cross-functional team and collaborate with front-end engineers, quality engineers, product managers, and more.
The platform you help us build will scale novel functionality to millions of Plus users worldwide.
Our team strives to set the bar for real-time, high-scale, mission-critical trading systems. We want to work with people who are excited by this goal and have the talent to deliver on it.
What Youll Do - Responsibilities:
Containerize and deploy ML models at scale.
Build and maintain CI/CD pipelines for automated model training, testing, and deployment.
Work with data engineers to integrate streaming/batch data into feature pipelines
Design and build scalable, high-availability mission-critical systems and APIs
Drive the migration of large-scale, distributed trading services towards cloud-native microservices
Tackle technical challenges - performance, fault-tolerance, security, and live production issues
Work closely with product, DevOps\SRE, and infrastructure teams - we practice full-cycle development where developers own and operate what they build.
Requirements: 3+ years building backend services, with experience in ML frameworks (e.g., TensorFlow, PyTorch, ML.NET). While building SaaS applications, preferably in a service-oriented architecture
Hands‑on expertise with MLOps tooling (e.g., MLflow, Kubeflow, TorchServe, KFServing).
Familiarity with cloud‑native ML offerings (AWS SageMaker, GCP AI Platform, Azure ML).
Bachelors Degree in Computer Science, Software Engineering, or equivalent.
Experience in writing optimized SQL and working against various different datastores.
Demonstrated success with scalable web applications or messaging systems
Experience with web security is a plus.
Experience fine‑tuning LLMs or large models using parameter‑efficient methods (LoRA, adapters) is a plus.
LLM fine‑tuning experience (HuggingFace, OpenAI, etc.) is a plus.
Expertise in modern web development frameworks, C#, Java, or equivalent is a plus.
This position is open to all candidates.