1 day ago
San Diego, CA, USAEntry Level / Mid Level
H1B sponsor
Base Salary
$117k - $175k/yr
Responsibilities
- Design, build, test, and operate production ML components and services.
- Build pipelines for data preparation, feature engineering, model training, evaluation, deployment, and monitoring.
- Develop APIs and services integrating ML capabilities into web, mobile, and backend applications.
- Write maintainable, tested Python code using version control, code review, automated testing, and debugging practices.
- Train, evaluate, deploy, manage, and retrain ML models using appropriate machine learning and statistical techniques.
- Monitor production ML systems and troubleshoot data quality, model performance, reliability, scalability, and cost.
- Collaborate with Data Scientists, ML Engineers, Data Engineers, Software Engineers, and Product partners to productionize prototypes and requirements.
- Evaluate technical approaches, communicate implementation choices and trade-offs, and own defined components through production support.
- Contribute to engineering standards, documentation, continuous improvement, and knowledge sharing.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related technical field, or equivalent practical experience.
- 1–2 years of professional experience in Machine Learning Engineering, Data Engineering, Software Engineering, or a similar role, including production ML experience or equivalent demonstrated experience.
- Working knowledge of production ML lifecycle activities including data and feature pipelines, training, evaluation, inference, APIs, deployment, continuous training, and monitoring.
- Strong Python and software engineering fundamentals, including pandas, NumPy, and scikit-learn.
- Experience with relational SQL databases and at least one NoSQL or distributed data technology.
- Hands-on experience training, evaluating, and serving ML models through APIs or batch-processing services.
- Experience with workflow orchestration such as Airflow, a major cloud platform such as AWS, Docker, and Git-based CI/CD.
- Ability to monitor and troubleshoot production services, pipelines, and model behavior.
- Clear written and verbal communication across technical and non-technical audiences.
- Preferred experience includes Amazon SageMaker, MLflow, Kubernetes, Amazon EKS, Snowflake, Kafka, Flink, model explainability, responsible AI, bias or fairness assessment, large language models, retrieval-augmented generation, LangChain, LangGraph, healthcare, medical devices, or privacy-sensitive data environments.
Benefits
- Medical, dental, vision, life, AD&D, and disability insurance.
- HSA, FSA, commuter benefits, and sleep care management.
- 401(k), ESPP, EAP, and tuition assistance.
- Flexible time off for salaried employees, 11 paid holidays, and 3 floating holidays.
- Up to 14 weeks of primary caregiver leave or 2 weeks of secondary caregiver leave.
- Flexible work arrangements and professional growth programs are provided.
- Compensation varies by geographic location, qualifications, experience, skills, and internal equity; the stated pay range is $117,000–$175,000 USD annually.
Tech Stack
Apache AirflowApache FlinkApache KafkaAWSDockerGitKubernetesMLflowNumPyPandasPythonscikit-learnSnowflakeSQL
Categories
About ResMed
We believe shaping a better world starts with better sleep and breathing, which is why we pioneer innovative solutions to help millions of people in more than 140 countries around the world live happier, healthier lives. Our AI-powered digital health solutions, cloud-connected devices and intelligent software make home healthcare more personalized, accessible and effective.