$90,000 to $115,000; not specified; health benefit...
Hybrid
Python, pandas, numpy, scikit-learn
Ml pipelines and services
Model deployment and monitoring
Assist in designing and implementing ML pipelines and services in cloud and on-premise environments
Job Summary
Assist in designing and implementing ML pipelines and services in cloud and on-premise environments.
Support model deployment, monitoring, and performance optimization, applying MLOps practices such as CI/CD, model versioning, and retraining workflows.
The salary band for this position ranges from $90,000 to $115,000, with a compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
Matching Summary
Assist in designing and implementing ML pipelines and services in cloud and on-premise environments.
Salary
$90,000 to $115,000; Not specified; Health benefits, retirement savings, share plan, personal wellness, volunteer opportunities
Skills & Requirements
Must-have
Python, Pandas, NumPy, scikit-learn
ML pipelines and services
Model deployment and monitoring
MLOps practices (CI/CD, versioning)
Snowflake and AWS services
Linux-based systems
Strong SQL skills
Nice-to-have
Apache Spark and Snowpark
Cloud platform exposure
Data privacy and security adherence
Collaboration and knowledge sharing
Key Requirements
Bachelor's degree in Computer Science, Data Science, Engineering, or related field
2–4 years of experience in machine learning engineering
Basic experience with Jenkins and Docker
Exposure to ML workflow tools (MLflow, Airflow) is a plus