Senior Machine Learning Engineer

About this role

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Skills you'll use

What you'll do

• 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.
• Monitor, detect, and mitigate risks unique to LLMs and agentic systems.
• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking.
• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path.

Who can apply

• Deep understanding of SOTA ML model architectures, especially language models
• Understanding of data pipelines, feature stores, and model lifecycle
• Experience in performance engineering: developing high-throughput, low-latency systems
• Experience with continuous integration, writing testable code, and test-driven development
• Deep understanding of algorithms, data structures, scalability, and distributed systems
• Privacy, authorization/authentication engineering is a huge plus.
• Experience with NLP, recommendation systems, or computer vision
• Exposure to MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, Vertex AI)

Perks & benefits

About Skyflow

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