Staff Machine Learning Engineer
New
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AngiHome services
Remote - United StatesFull-TimeStaff
SalaryThe base salary band for this position ranges from $230,000-$310,000
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonSQLMachine LearningPyTorchTensorflowDeep LearningMLOpsDistributed Systems
Requirements
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 6+ years of experience in data science and machine learning, preferably in tech or marketplace environments.
- Hands-on experience post-training and self-hosting open-weight LLMs including fine-tuning, quantization, and serving infrastructure like vLLM or SGLang.
- Deep understanding of evaluation metrics for deep learning and classical ML, including the ability to design strategies to catch regressions.
- End-to-end fluency in the MLOps lifecycle, including data versioning, feature stores, CI/CD, and model observability.
- Knowledge of large-scale distributed application architecture, design, and performance tuning.
- Proven ability to drive the roadmap and direction of scalable, production-quality systems.
- Practical knowledge of advanced machine learning and deep learning for search and information retrieval.
- Proficiency in Python, SQL, and ML frameworks such as TensorFlow and PyTorch.
- Excellent communication skills for conveying complex technical concepts to non-technical stakeholders.
Responsibilities
- Lead development of advanced machine learning and AI models to improve marketplace algorithms such as search ranking, recommendation, and matching solutions.
- Design and architect robust MLOps practices to ensure seamless deployment and scalability of machine learning models, including self-hosted LLMs.
- Automate model training, post-training, and inference optimization while owning the full MLOps lifecycle from data pipelines to production monitoring.
- Define and own rigorous evaluation frameworks for deep learning and ML systems, including A/B testing and LLM-specific evaluation.
- Collaborate with engineering, data science, and product management teams to integrate scalable machine learning solutions into products.
- Drive the technical vision and roadmap for machine learning initiatives.
- Mentor junior team members and foster a culture of technical excellence.
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