Machine Learning Applied Engineer

"About the job

Basic Qualifications

• Master’s degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis. We will also consider candidates with a relevant bachelor’s degree in a STEM field with 10+ years of relevant work experience in Machine Learning and Statistics.

• Very strong experience in AI and ML.

• Proven track record in building and deploying machine learning models, with a strong understanding of the theory and tradeoffs behind these techniques.

• Proficiency in statistical and machine learning techniques for predictive modeling, classification, and regression.

• Very strong knowledge of Python and SQL.

• Strong experience with AWS cloud services and tools, including AWS SageMaker for model development, training, and deployment, as well as AWS Bedrock for building and fine-tuning foundation models.

• Experience in working with model registry tools such as MLflow, SageMaker Model Registry, or other similar systems, to track, version, and manage machine learning models throughout their lifecycle.

• Experience implementing DataOps, MLOps, and/or DevSecOps in the AI, ML, and software development lifecycle.

• Experience building ML models with PyTorch, Scikit-learn, and GenAI models.

• Experience working with LLM frameworks such as HuggingFace libraries and with agent-based frameworks such as LangChain and Mirascope.

• Familiarity with Snowflake for cloud data warehousing, data integration, and efficient handling of large-scale data storage and processing.

Above and Beyond

• PhD degree in mathematics, statistics, economics, computer science, or other quantitative disciplines with a focus on data analysis.

• Experience in the FinTech or PropTech areas.

• Experience in a startup environment.

• Experience with microservices.

• Experience working with data governance policies in SOC2 or similarly certified organizations.

Key Technologies We Use

• Backend: Go, Python.

• Cloud: Amazon Web Services (AWS).

• Data: MongoDB, PostgreSQL, S3, Sagemaker, Snowflake, Tableau.

• Frontend: React, Typescript.

• Mobile: Flutter, Dart."

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