PN - MLOPS ENGINEER | TEPLATIPLÁN
Descripción de la oferta de empleo
In this role, you will bridge the gap between data science and operations by building and maintaining automated infrastructure, pipelines, and processes for deploying and monitoring machine learning models in production environments.
You will also contribute to creating data collection and labeling software.
ey ResponsibilitiesInfrastructure Development.
Build tools to streamline preprocessing, model training, and validation for ML engineers.
Start with AWS infrastructure and transition to third-party tools or in-house solutions as necessary.
Develop infrastructure to enable seamless transitions between cloud and edge environments for training and inference.
ollaboration.
Work closely with clinical partners and teammates across the United States.
esign and Architecture.
Create detailed architecture/design documents for owned components and participate in risk management and Threat Model Analysis (TMA).
ackend Development.
Develop dashboards, data pipelines, and infrastructure tailored to the ML team's unique requirements.
odel Deployment.
Design scalable systems for training and inference, including CI/CD pipelines and automation tools for deploying machine learning models.
uality Assurance.
Develop automation frameworks, test plans, and unit/integration tests.
Collaborate with QA teams for system testing.
eam Support.
Conduct timely design and code reviews and support peer testing.
egulatory Compliance.
Research and adhere to software development processes mandated by regulatory authorities.
kills and Expertise5+ years of experience creating ML infrastructure for deep learning models with large-scale data; 10+ years of software engineering experience.
eep expertise with AWS, including services such as SageMaker Studio, Kinesis, S3, EC2, Lambda, CloudWatch, EMR, and Elastic Docker Container.
trong understanding of ML concepts, including model selection, deep learning architectures, and hyperparameter tuning.
Experience with modern ML frameworks such as PyTorch, TensorFlow, NumPy, and Scikit-learn.
Knowledge of AI/robotics frameworks like OpenCV, ROS2, and Kaldi is preferred.
xperience in data engineering with distributed processing and training.
amiliarity with MLOps frameworks like Kubeflow, MLFlow, and Airflow.
roficiency with containerization and orchestration tools like Docker and Kubernetes.
nowledge of A/B testing and benchmarking model performance in production.
xpertise in Python and related ML libraries; working knowledge of C++ is preferred.
xperience in PyQt user interface development or willingness to learn.
ackground in IoT, edge computing, and/or robotic systems is a plus.
nowledge of HIPAA compliance and developing software/AI for medical devices is advantageous.
hy Join Us?We are a fast-moving, well-funded organization working on innovative technologies to improve lives
Detalles de la oferta
- Sin especificar
- 30/12/2024
- 30/03/2025
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