Description
Machine Learning Platform Software Engineer
Job description
- Collaborate with data engineers, data scientists, and product teams to guide the translation of R&D prototypes into stable, testable, and maintainable production services
- Develop and deploy tools and services for our team to accelerate the production lifecycle and assessment of production readiness
- Help lead team members in executing continuous integration and continuous delivery (CI/CD) activities to release code into a Production environment
- Act as a consultant within the Science Organization on software engineering principles, code quality, and performance optimization techniques
- Apply software engineering rigor and best practices to machine learning, including CI/CD and automation
- Build model performance monitoring capabilities and data monitoring tools
Requirements
- MS Computer Science, Engineering, Technology, Mathematics, Statistics, or related field with 3+ years of industry experience or BS + 5 years' experience
- Hands on coding experience with Python building end-to-end systems as an MLOps Engineer, Machine Learning Engineer, Software Engineer, or equivalent
- Experience in ML model development, orchestration, deployment, monitoring, support and creating and maintaining deployment pipelines with CI/CD tools
- Experience with cloud computing platforms like AWS, GCP, or other cloud providers developing with containers (e.g., Docker, Kubernetes) in cloud computing environments
- Experience with database, such as SparkSQL, MongoDB, SQL, and SQLite
Preferred:
- Exposure to deep learning approaches and modeling frameworks (Py Torch, TensorFlow, Keras, etc.)
- Experience building ML web service, such as Flask, JavaScript, HTML, and Django.· Familiarity with Kubeflow or similar platforms like MLflow or SageMaker
- Experience building and evaluating machine learning models
- Strong understanding of software testing, benchmarking, and continuous integration
- Experience mentoring and teaching software development best practices to data scientists
- Ability to translate complex technical concepts to collaborations, decision makers, and non-technical audiences
The ideal candidate will have a passion for generating new ideas, be a proactive and quick learner, and be able to demonstrate creativity and innovation.
Location
San Diego, California
Contact
Kneron
Artificial Intelligence
Internet of Things
Machine Learning
Robotics
Software
2 applies
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