Senior Machine Learning Engineer I

About the job

The Machine Learning Engineer develops, deploys, and maintains scalable AI/ML solutions that meet production standards. They turn data science prototypes into reliable, production-ready services, automate MLOps workflows, and build tools and infrastructure for model training and inference. This role requires strong software engineering, DevOps, and cloud skills, as well as experience with NLP, search technologies, vector and graph databases, and modern MLOps platforms.

Key responsibilities

Transform data science experiments into scalable production-ready AI services Enable both offline model training and real-time inference through robust model serving pipelines. Automate end-to-end MLOps workflows and develop internal ML tools. Monitor production data quality, model versions, cloud costs, and security compliance. Support and maintain infrastructure that empowers the data science team.

Technical skills

Proficient in general software engineering principles and practices. Skilled in DevOps and cloud-based engineering environments. Experience with NLP, search technologies, and modern ML toolkits. Familiar with search engines, vector databases, and graph databases. Hands-on experience with MLOps platforms and automation tools. Hands-on experience with Retrieval-Augmented Generation (RAG) and AI agentic solutions, with a strong focus on engineering and productionization.

Common tools and technologies

Docker, Kubernetes, Python, Flask/ FastAPI, Redis, Solr/ElasticSearch, Weaviate/Qdrant, Neo4j/AWS Neptune/DGraph,  AWS/Azure/GCP, MLFlow/KubeFlow/Weights & Biases, TorchServe/Ray Serve/Triton/AWS SageMaker

U.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates.

This job is eligible for an annual incentive bonus.

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