Back End Engineer (Node, Machine Learning)

FusionHit

Costa Rica
Autónomo
Tiempo completo

Hace 29 días
Postúlese fácilmente

We are looking for a Senior Backend Engineer to join our client's fast-paced, dynamic environment. This is more than just a backend or MLOps position — it’s a chance to shape the future of one of the most ambitious genealogical preservation efforts in the world. You will help design, build, and operationalize robust backend systems and machine learning infrastructure to validate and protect millions of oral history records collected across Africa. Your work will directly contribute to preventing fraud, ensuring data authenticity, and advancing AI adoption for meaningful social impact.Location: Must reside and have work authorization in Latin America.
Availability: Must be available to work with significant overlap with Mountain Standard Time (MST).The Ideal Candidate Has:

BS/MS in Computer Science, Information Technology, or related field with 7+ years of backend development experience (Node.js preferred, Python, Go, or Java also considered).
Hands-on experience deploying and maintaining machine learning models in production (PyTorch, TensorFlow, or Hugging Face).
Experience customizing and fine-tuning pre-trained models for specific use cases.
Strong grasp of API design (REST/gRPC) and scalable system architecture.
Proficiency in CI/CD pipelines, observability, and rollback strategies.
Experience with containerization (Docker) and orchestration tools (Kubernetes).
Comfortable collaborating with data scientists, UX designers, and product teams.
Creative and curious mindset with a willingness to propose innovative approaches.
Excellent communication skills in English (C1 preferred, strong B2 may be considered).
Nice to have: Experience with MLOps tools (LangChain, MLFlow), A/B testing, streaming platforms (Kafka, Google Pub/Sub), or work on fraud detection/sensitive data projects

Key Responsibilities:

Build and maintain scalable backend services in Node.js that power fraud detection algorithms and ML-based features.
Deploy and operationalize machine learning models with robust architecture, CI/CD automation, and monitoring.
Collaborate with ML and data science teams to fine-tune and integrate models into production systems.
Design secure, high-performance APIs that expose ML functionalities.
Develop tools to validate records using multiple media formats (audio, documents, images).
Contribute creative technical solutions to problems involving data authenticity and fraud prevention.
Ensure stability and smooth rollout during major product updates.

FusionHit