Machine Learning Engineer
New
T
TwilioCommunications Technology
United States; not eligible to be hired in CA, CT, NJ, NY, PA, WAFull-TimeMiddle
SalaryUSD 155520 - 228700 / year
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPythonSQLJavaKubeflowKubernetesAirflowApache KafkaSparkMLOps
Requirements
- Strong foundation in ML/AI including statistics, probability, and optimization.
- 5+ years of experience building, deploying, and operating data and ML systems in production.
- Proficiency in Python, Java, and SQL.
- Strong software engineering fundamentals (system design, testing, version control, code reviews).
- Hands-on experience with workflow orchestration and data pipelines (e.g., Airflow, Kubeflow).
- Experience with cloud data platforms and storage (e.g., SageMaker Feature Store, Snowflake, DynamoDB, OpenSearch).
- Experience with ML lifecycle and MLOps tooling (e.g., MLflow, Metaflow, LLM/agent frameworks like LangChain/LangGraph).
- Working knowledge of containerization and cloud infrastructure (Docker, Kubernetes).
- Experience with GitOps/CI/CD tools (e.g., Argo CD).
- Understanding of data modeling, distributed computing, and streaming frameworks (e.g., Spark/EMR, Flink, Kafka Streams).
Responsibilities
- Partner with product, UX, and technical stakeholders to analyze business problems and define measurable ML problem statements.
- Design, implement, and maintain scalable, enterprise-grade ML solutions in production.
- Build reproducible ML workflows for data preparation, training, evaluation, and inference using modern orchestration and MLOps tooling.
- Implement monitoring and evaluation frameworks to improve data quality, model performance, latency, and cost.
- Collaborate cross-functionally with Product, Data Science, Engineering, and Security to deliver compliant ML-powered services.
- Own operational excellence including SLAs, on-call, incident response, and blameless post-mortems.
- Drive engineering excellence via AI-assisted SDLC, code reviews, and MLOps best practices.
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