Machine Learning Engineer
Sumo Logic
NumpyPandasPythonScikit-Learn
Machine Learning Engineer
RADAR
full-time
Posted on:
Location Type: Remote
Location: Remote • California • 🇺🇸 United States
Visit company websiteSalary
💰 $120,000 - $190,000 per year
Job Level
JuniorMid-Level
Tech Stack
AirflowAWSAzureBigQueryCloudKafkaPythonPyTorchScikit-LearnSparkSQL
About the role
- Build and scale ML infrastructure: Design and maintain scalable, reliable and efficient production pipelines for feature engineering, training, prediction and model serving using tools including Airflow, Big Query and Kubeflow
- Drive model performance: Train, validate and deploy high-quality ML models, applying advanced techniques in feature selection, hyperparameter tuning and model architecture choices to improve the accuracy of our products
- Accelerate ML development: Optimize feature engineering pipelines for performance and scalability while collaborating with Data Science to research, develop, and deploy new features that improve model accuracy
- Ensure reliability: Implement comprehensive model monitoring, automated training pipelines, and observability solutions to maintain model health and performance
- Champion best practices: Apply CI/CD principles including automated testing, model validation, and deployment strategies
Requirements
- 2+ years building production ML systems at scale, including feature engineering, training, deployment, and monitoring
- Strong proficiency in Python and ML frameworks (scikit-learn, PyTorch, XGBoost)
- Hands-on experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML)
- Expertise in big data processing including SQL optimization and distributed computing (Spark/Dask)
- Production experience with workflow orchestration tools (Airflow, Dagster, Prefect)
- Proficiency with version control (Git) and CI/CD practices
- Experience with real-time streaming data (Kafka, Flink, Pub/Sub.)
- Bachelor's degree in Computer Science, Statistics, or related field
- Experience with MLOps tools (MLflow, Weights & Biases, etc.)
Benefits
- equity
- comprehensive medical and dental coverage
- life and disability benefits
- 401k plan
- flexible time off
- paid parental leave
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Pythonscikit-learnPyTorchXGBoostSQL optimizationSparkDaskGitCI/CDMLOps
Soft skills
collaborationproblem-solvingattention to detailcommunicationadaptability
