ML Engineer

Implement and deploy machine learning models that drive measurable impact for our clients.

Partner with stakeholders to propose innovative solutions to existing business problems.

Own the full end-to-end machine learning delivery lifecycle, including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployment, and maintenance.

Create tools, frameworks, and libraries that accelerate the delivery of our ML products and improve our workflows.

Actively participate in our AI and ML community, fostering a culture of learning and experimentation.

Qualifications

We'd love to hear from you if you...

Have an advanced degree in Computer Science, Mathematics, or a similar quantitative discipline.

Are proficient with Python

Have a broad understanding of data extraction, data manipulation, and feature engineering techniques.

Are familiar with statistical methodologies.

Have experience in productionizing machine learning models.

Have knowledge of DevOps technologies such as Docker and ML Ops practices and platforms like MLflow.

Have experience with agile delivery methodologies and CI/CD.

Have strong communication skills.

Nice to have

Understanding of NLP algorithms and techniques.

Experience with Large Language Models (fine-tuning, RAG, agents), using Open AI APIs.

Experience with cloud infrastructure.