Remote Senior ML Engineer, Production-Grade AI Systems

North Eastern Services; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Fusemachines is seeking a Senior Machine Learning Engineer to architect, build, and deploy high-performance ML systems across the tech stack. You will handle end-to-end ML lifecycle from data processing to low-latency model deployment, emphasizing scalable, production-ready code and real-time APIs.

You must combine applied ML expertise with production software engineering skills, ensuring latency, throughput, and reliable monitoring in a remote, full-time role.

Qualifications

• 5–8+ years of experience as a Machine Learning Engineer or Software Engineer focusing on ML systems, ideally within Ad Tech, MarTech, or high-scale recommendation systems.
• Production Engineering Skills: Strong software engineering fundamentals (OOP, data structures, algorithm design). Expert-level Python and strong proficiency in a compiled or high-performance language (e.g., C++, Java, Scala, Go, or Rust).
• ML Systems & Serving: Deep experience deploying machine learning models into highly concurrent, low-latency production environments (APIs, microservices, Triton Inference Server, custom containers).
• Distributed Computing: Hands-on experience with big data processing (Apache Spark, Kafka, Flink) and complex SQL queries.
• Core ML & Deep Learning: Proven track record of shipping both tree-based models and neural networks (PyTorch/TensorFlow) to production.
• Statistics & Experimentation: Solid grasp of statistics, hypothesis testing, and rigorous A/B experiment design.

Responsibilities

• Scale Data Engineering & Feature Pipelines: Process and extract features from massive, highly sparse datasets using SQL, Python, and distributed computing frameworks (e.g., Spark, Ray).
• Architect offline and online feature pipelines. Manage real-time feature computation and low-latency feature stores ensuring zero online/offline skew.
• Perform rigorous missingness analysis, leakage checks, and handle high-cardinality categorical variables safely.
• Train, tune, and scale supervised learning models, utilizing advanced gradient boosting and Factorization Machines.
• Design and implement Deep Learning architectures for structured/recommendation data using PyTorch or TensorFlow.
• Apply rigorous tabular modeling practices: meticulous leakage prevention, class imbalance strategies, and robust cross-validation on time-split data.
• Write clean, object-oriented, and modular production code. Transition models from Python research environments to high-performance serving environments (packaging with ONNX, TensorRT, etc).
• Design and maintain robust MLOps pipelines: automated model retraining, versioning, shadow deployments, and CI/CD for machine learning.
• Monitor production models for data drift, concept drift, and performance degradation in real-time, implementing automated alerting and fallback mechanisms.
• Design rigorous A/B and multivariate tests to measure the true business incrementality of ML models.

Skills

ML System Design

Production-grade Python

Distributed Systems

Model Deployment

MLOps

A/B Testing

Tools

PyTorch

TensorFlow

XGBoost

LightGBM

Spark

ONNX/TensorRT

Ray

Job description

Fusemachines is seeking a Senior Machine Learning Engineer to architect, build, and deploy high-performance ML systems across the tech stack. You will handle end-to-end ML lifecycle from data processing to low-latency model deployment, emphasizing scalable, production-ready code and real-time APIs.

You must combine applied ML expertise with production software engineering skills, ensuring latency, throughput, and reliable monitoring in a remote, full-time role.