ML Engineer

Sourced from linkedin.com

MetAntz is seeking an experienced ML Engineer to own the end-to-end ML lifecycle for real products, including data ingestion, feature design, model selection, training, deployment, monitoring, and iteration. You will build production-grade ML systems with PyTorch or TensorFlow, apply GenAI and LLM work where it creates measurable value, and establish MLOps foundations. This role offers meaningful ownership over core AI systems and requires 7+ years of hands-on ML engineering experience.

• End-to-end ML lifecycle ownership across real products: data ingestion, feature design, model selection, training, deployment, monitoring, iteration, no handoffs.
• Build production-grade ML systems with PyTorch or TensorFlow with attention to latency, reliability, cost, and failure modes.
• Apply GenAI and LLM work (fine-tuning, RAG, prompt orchestration, evaluation, guardrails) where it creates measurable value.
• Establish MLOps foundations: model versioning, CI/CD, automated testing, deployment pipelines, serving layers, monitoring, A/B experimentation.
• Partner with product engineering and data to translate fuzzy business problems into tractable ML solutions and quantify impact.
• Provide technical leadership through code reviews, model reviews, mentoring, and raising the bar for ML engineering discipline.
• Own incident response: debug production failures, data drift, performance regressions, and bias issues.