TL;DR

Machine Learning Engineer (AI): Leading the design and development of low-latency Algo inference services and scaling robust real-time decisioning engines with an accent on seamless model deployment, versioning, and A/B testing at runtime. Focus on continuously optimizing latency, throughput, and cost-efficiency in high-performance ML inference systems.

Location: Remote

Company

%hirify_global% is a Software Development Company specializing in various IT solutions.

What you will do

Lead the design and development of low-latency Algo inference services handling billions of requests per day.
Build and scale robust real-time decisioning engines, integrating ML models with business logic.
Collaborate closely with Data Science to ensure reliable and seamless model deployment into production.
Design systems for model versioning, shadowing, and A/B testing at runtime.
Guarantee system scalability, high availability, and comprehensive observability.
Continuously optimize latency, throughput, and cost-efficiency using modern tooling and techniques.

Requirements

5+ years in high-performance backend/ML inference systems.
Expertise in Python, low-latency APIs and real-time serving frameworks (FastAPI, Triton Inference Server, TorchServe, BentoML).
Experience with scalable service architecture, message queues (Kafka, Pub/Sub), and async processing.
Deep understanding of model deployment practices, online/offline feature parity, and real-time monitoring.
Experience in cloud environments (AWS, GCP, or OCI) and container orchestration (Kubernetes).
Experience working with In-memory and NoSQL databases (e.g., Aerospike, Redis, Bigtable).
Experience with observability tools (e.g., Prometheus, Grafana, OpenTelemetry) for monitoring, alerting, and troubleshooting.
B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related field.

Culture & Benefits

Remote work options available.
Operate autonomously and collaborate effectively with cross-functional teams.