As a Sr. ML Engineer, you will be responsible for building automation and model development, deployment, and serving to optimize time to market and quality of AI/ML applications. Specifically, you will give architectural guidance to ensure our global AI/ML systems are production-grade, scalable and use the latest state-of-the-art technology and methodology. You will help define and ensure the best coding practices within the team of excellent and engaged engineers. You will be given creative freedom and opportunities to work on advanced AI/ML problems, such as reinforcement learning and a self-serve AI/ML platform. You will do hands-on code development, mentor junior team members, and interact with business stakeholders. At ResMed, we are dedicated to a diverse team and inclusive work environment.
- Build and Design the creation and maintenance of optimal global AI/ML architectures.
- Stay informed of industry trends and enable successful AI/ML solutions by leveraging best practices.
- Partner effectively with stakeholders and business users.
- Participate in and set up Proof of Concepts (POCs) to demonstrate proposed solutions.
- Enable team members in the MLE space through training, culture, and team building.
- Identify, design, and implement internal process improvements: Automating manual processes, re-designing infrastructure for greater scalability, etc.
- Build infrastructure needed for AI/ML systems, such as model inference, automated (re-)training, monitoring, explainability, etc.
- Work with stakeholders including the Executive, Product, Data, and Design teams to help with AI/ML-related technical issues and support their AI/ML infrastructure needs.
- You will build MVP applications to showcase the value of AI/ML models, owning the end-to-end process.
- You'll develop & deploy reusable production-grade functionality and automation around AI/ML feature pipelines, real-time/batch inference, continuous training, and model monitoring.
- You will participate in design sessions with the team to solve leading-edge AI problems and present insights to various/all levels of the company.
- Actively handle escalated incidents to resolution and suggest solutions to limit future exposure.
- Participate in Code Review and process improvement.
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- Bachelor/Master/Engineering degree in IT/Computer Science/software engineering or relevant field.
- 6+ years of total experience in a complex, technical environment.
- Hands-on experience in building scalable AI/ML Models/Systems for continuous training automation, computer vision, natural language processing, or similarly advanced AI/ML problems.
- Hands-on experience in the following AWS (Amazon Web Services) cloud services: SageMaker, ECR/EC2 Kubernetes/ECS and Docker, AWS Batch processing, Lambda, Glue, EventBridge, Airflow, MLFlow, Step Functions, etc.
- Hands-on experience with developing production-grade Scala & Python.
- Hands-on experience with infrastructure as code using Terraform.
- Hands-on Experience with Dev ops(CICD) & ML Ops services/tools.
- Experience with big data tools such as EMR (Elastic MapReduce), Spark or similar.
- Experience with relational SQL and NoSQL databases.
- Experience leading, supporting, and working with cross-functional teams in a dynamic environment.
- All listed duties, requirements and responsibilities are considered as essential functions to this position; however, business conditions may require reasonable accommodation for added tasks and responsibilities.