AI-First ML Engineer II — Production-Ready & Impact

Mimecast North America, Inc.; Minneapolis (MN); On-site; USD 120,000 - 180,000; Full time

Job summary

Mimecast is seeking a Machine Learning Engineer II for the Incydr Product Development team. You will own end-to-end machine learning initiatives, from data wrangling to model deployment, and collaborate with cross-functional teams to deliver value to customers and strengthen insider risk management capabilities.

You will contribute to AI-first engineering by designing scalable architectures, deploying models, and monitoring performance at scale, while mentoring peers and driving best practices

Qualifications

• Ph.D. or Master’s degree in a quantitative field with practical ML application experience.

Responsibilities

• Research, design, develop, and maintain ML models optimized for accuracy and throughput.
• Train, evaluate, and fine-tune models with best practices.
• Design end-to-end data and ML pipelines for real-time data products.
• Deploy models and monitor performance in production.
• Lead ML projects from conception to deployment.
• Mentor junior team members and promote best practices.
• Collaborate with Product, Engineering, Marketing, and Sales to deliver customer value.
• Communicate complex concepts clearly to non-technical stakeholders.

Skills

Python

C++

Java

Kotlin

Statistical reasoning

ML deployment

Problem solving

Communication

Education

Ph.D. or Master’s degree in quantitative discipline

Tools

PyTorch

NLTK

SpaCy

OpenCV

Tesseract

HuggingFace

LangChain

LlamaIndex

n8n

SpringAI

AWS (ECS, Kinesis, Lambda, S3, Glue, Sagemaker, Bedrock, Athena, RDS, Redshift)

IaC (infrastructure-as-code)

Version control

Job description

Mimecast is seeking a Machine Learning Engineer II for the Incydr Product Development team. You will own end-to-end machine learning initiatives, from data wrangling to model deployment, and collaborate with cross-functional teams to deliver value to customers and strengthen insider risk management capabilities.

You will contribute to AI-first engineering by designing scalable architectures, deploying models, and monitoring performance at scale, while mentoring peers and driving best practices