Senior ML Engineer — Production AI/NLP Pipelines

Openkrill; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Work from home expense

Excellent Health Insurance Options

Very generous PTO

Flexible Hours

Job summary

Skyflow is seeking a Senior Machine Learning Engineer to build, deploy, and scale ML models that directly impact product and business outcomes. You'll work closely with product, backend, and data teams to turn real-world problems into production-ready ML solutions.

This hands-on role emphasizes experimentation, ownership, and shipping. The ideal candidate has hands-on experience building end-to-end ML systems, deploying models to production, creating AI workflows, and improving observability and

Qualifications

• 8+ years of experience in Machine Learning.
• Proficient in one of the programming languages either Go or Python.
• Design, develop, and deploy production ML models and AI services.
• Build end-to-end ML pipelines for data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
• Having experience in implementing AI-driven software systems with a focus on NLP, NER.
• Hands‑on experience with Python and ML libraries (NumPy, Pandas, Scikit‑learn).

Responsibilities

• Design, build, train, and deploy machine learning models for production use.
• Build end-to-end ML pipelines: data ingestion, feature engineering, training, evaluation, deployment.
• Experimenting with and rapid prototyping of open source ML models.
• Fine tuning open source models for NLP and Vision tasks.
• Synthetic data generation, model validation.
• GPU Performance optimisation of large scale ML models, including transformers.
• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality.

Skills

ML experience

Python

Go

NLP/NER

ML pipelines

ML libraries

Observability/Monitoring

CI/CD

Tools

TensorFlow

PyTorch

Docker

Kubernetes

MLflow

SageMaker/Vertex AI

Job description

Skyflow is seeking a Senior Machine Learning Engineer to build, deploy, and scale ML models that directly impact product and business outcomes. You'll work closely with product, backend, and data teams to turn real-world problems into production-ready ML solutions.

This hands-on role emphasizes experimentation, ownership, and shipping. The ideal candidate has hands-on experience building end-to-end ML systems, deploying models to production, creating AI workflows, and improving observability and