Senior Machine Learning Engineer

at  ResMed

Let’s talk about the team
Join our Center of Excellence for Generative AI Team as a Senior Machine Learning Engineer ( MLE ) to advance Generative Artificial Intelligence (Gen AI) and Machine Learning (ML) initiatives that drive our business in an “AI First” approach. ResMed’s commitment to improving the lives of sleep apnea patients through our extensive sleep data offers unparalleled opportunities for AI/ML innovation. In this role, you’ll spearhead projects that transform patient care, provider experience, and operations efficiencies through AI.
Let’s talk about the role
As a Senior MLE, you’ll not only build production-grade generative AI applications, but also develop guardrails, perform model benchmarking, and foster best practices. This involves transforming technical specs into AI/ML systems, encompassing development, testing, and monitoring. You’ll work closely with management, product management, and delivery functions to help develop technical roadmaps. You’ll help drive the adoption of generative AI across the organization by consulting product teams on their generative AI products and communicating the opportunities and limitations of generative AI to a broad audience of stakeholders. You will be working with high-achieving teammates in a global team .

Let’s talk about responsibilities

• Work in a high-performing team to design and implement cutting-edge internal and external generative AI products .
• Develop guardrails, benchmarks, and best practices around generative AI .
• Spearhead the creation of POC and MVP applications to demonstrate AI/ML model value .
• Develop and deploy scalable, production-grade AI/ ML.
• Facilitate design sessions to address complex AI challenges, offering insights to various company levels .
• Collaborate with cross-functional stakeholders from product management, operations, and data science to develop and deploy scalable production models .
• Mentor junior team members and foster best coding practices .

Let’s talk about qualifications and experience

QUALIFICATIONS

• Either: Masters or PhD in computer science, data science, or other quantitative field and 3+ years of industry experience in Machine Learning Engineering, Data Science, Data Engineering, or related fields.
• Or: 5+ years of industry experience in Machine Learning Engineering, Data Science, Data Engineering, or related field s .
• Extensive experience with Machine Learning systems, including feature/data pipelines, model training, and inference .
• Experience with natural language processing, including text processing, regex, feature engineering, and modeling .
• Expertise in Python coding .
• 5+ years of experience with AWS or other cloud platforms .
• Solid track record of serving ML models in production .

PREFERRED QUALIFICATIONS

• Extensive experience in infrastructure tools like Terraform .
• Experience with DevOps (deployments, observability, model monitoring), unit tests, and best coding practices .
• Previous experience with generative AI .
• Advanced knowledge of RESTful APIs, and industry -standard architectural design patterns .

Let’s talk about what you can expect

• A supportive environment that focuses on people’s development and best implementation
• Opportunity to design, influence, and be innovative
• Work with inclusive global teams and the open sharing of new ideas . We want your ideas !
• Be supported both inside and outside of the work environment
• The opportunity to build something meaningful and see a direct positive impact on people’s lives !
• Dream big, iterate and experiment to drive innovation .

• Work in a high-performing team to design and implement cutting-edge internal and external generative AI products .
• Develop guardrails, benchmarks, and best practices around generative AI .
• Spearhead the creation of POC and MVP applications to demonstrate AI/ML model value .
• Develop and deploy scalable, production-grade AI/ ML.
• Facilitate design sessions to address complex AI challenges, offering insights to various company levels .
• Collaborate with cross-functional stakeholders from product management, operations, and data science to develop and deploy scalable production models .
• Mentor junior team members and foster best coding practices