Senior Machine Learning Engineer

Masters or PhD in Machine Learning, NLP, or related field
2+ years building and optimizing retrieval systems
2+ years training/fine-tuning transformer models
Deep understanding of LLMs, retrieval metrics and their trade-offs
Implement memory and tool-use strategies to enhance LLM-based agent capabilities
Experience building end-to-end systems as a Platform Engineer, MLOps Engineer, or Data Engineer
Strong understanding of software testing, benchmarking, and continuous integration
Build scalable, production-ready ML pipelines for training, evaluation, deployment and monitoring
Develop and implement CI/CD pipelines. Automate the deployment and monitoring of ML models.
Knowledge of query augmentation and content enrichment strategies
Expertise in automated LLM evaluation, including LLM-as-judge methodologies
Skilled at prompt engineering – including zero-shot, few-shot, and chain-of-thought.
Proven ability to balance scientific rigor with driving business impact

Optimizing LLM-based agents
Creating a platform for other teams to utilize ML capabilities
Deploying ML services to production
Measuring and improving retrieval systems across the spectrum from BM25 to semantic search
Developing comprehensive evaluation metrics to measure performance
Developing optimal chunking and enrichment strategies for diverse data sources
Exploring how different data types and formats impact retrieval performance
Building a platform for other teams to effectively utilize LLM tools and take advantage of prompt engineering
Developing APIs and scalable systems
Developing scalable tools and services to handle machine learning training and inference for clients
Writing zero-shot and few-shot prompts with structured inputs/outputs
Implementing benchmarking systems for prompts
Training and fine-tuning smaller, more efficient models
Creating labeled datasets
Conducting careful hyperparameter optimizations
Building automated training pipelines
Deploying and monitoring models in production
Optimizing model latency
Implementing comprehensive offline/online metrics to track performance