Machine Learning Engineer

Kalibri Labs

full-time

Posted on: 9/17/2025

Origin: • 🇺🇸 United States

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💰 $115,000 - $138,000 per year

Mid-LevelSenior

AirflowAWSBigQueryCloudDockerPythonPyTorchScalaSQLTensorflow

About the role

Partner with stakeholders throughout the organization to identify opportunities for leveraging company data to ensure quality, scalability and efficiency of Data Science solutions
Tune, operationalize, and deploy high quality AI/ML algorithms into Kalibri’s data platform
Build systems that setup, generate, and organize training data for online and offline models. Design, develop, and deploy models that integrate within Kalibri’s ecosystem
Work closely with data scientists to standardize, automate, and operate ML systems.
Coordinate with development and product functional teams to implement models and monitor outcomes
Maintain and expand existing AWS/Snowflake infrastructure with industry best practices, considering scalability, reliability, quality, and cost
Develop processes and tools to continuously monitor and analyze model performance and accuracy
Build automated quality tests and monitors that ensure availability, consistency, and accuracy
Participate in code reviews and design sessions within an Agile process paradigm

3+ years experience designing, building, and maintaining ML systems leveraging Data Science packages such as TensorFlow, scikit based packages, PyTorch etc, in a cloud based environment
2+ years of experience designing and implementing scalable systems and applications on cloud-based technologies
Expert SQL and Python programming in a production context
Experience owning a project across the full lifecycle to include design, development, deployment, and operations
Strong background in modern data warehouse technologies such as Snowflake, Databricks, BigQuery
SQL expertise in a modern data warehouse following an SQL-based ELT paradigm. Demonstrated ability to prepare for model deployment and integration into data pipelines with reactive, event-based systems
Confident working in container-based environments such as docker
Experience building ML pipeline using modern orchestration tools such as MLFlow, github actions, airflow, prefect, etc.
Bachelor’s Degree in Computer Science, Information Systems, or a related technical field, or equivalent work experience.