LP
Machine_Learning_Specialist / Data Scientist / AI Developer
LinkedIn Recruiter Post
We are seeking a Machine Learning Specialist / Data Scientist / AI Developer with 6+ years of experience in Python, R, SQL, and machine learning.
About the role
- Lead Software Engineer managing MLOps team within Sun Life’s Analytics Platform. Collaborating with various technical and business teams, focusing on AWS cloud services and machine learning operations.
Responsibilities
- Provide technical leadership for the MLOps squad within the Analytics Platform, influencing architecture and standards across multiple teams
- Design, build, and evolve production-grade MLOps and ML platform capabilities, including model lifecycle management, CI/CD, evaluation, monitoring, and governance
- Spend ~ 60% hands-on in software engineering, building high-quality, testable, maintainable services, frameworks, APIs, and shared libraries that enable ML and GenAI at scale
- Spend ~ 40% on platform, cloud, and MLOps enablement, ensuring solutions are secure, scalable, observable, and cost-effective
- Act as a technical authority for AWS-based ML platforms, leading design decisions and guiding adoption of new cloud and GenAI services
- Establish and evolve engineering and MLOps standards, patterns, and best practices across squads
- Partner closely with Architecture, Security, Risk, and Product teams to reduce delivery, operational, and model governance risk
- Lead by example through code reviews, design reviews, incident analysis, and operational improvements
- Mentor senior and intermediate engineers, raising the overall technical bar without direct people management
Requirements
- A deep software engineering background, with a strong track record of building and operating large-scale, production systems
- Extensive hands-on experience with AWS in production, including infrastructure design, deployment, and optimization
- Strong experience with Distributed systems and cloud-native architectures
- CI/CD pipelines and automation
- Observability, reliability, and incident response
- Practical experience with MLOps, ModelOps, ML platforms, or LLMOps in enterprise environments
- Proficiency in one or more of: Python, Java, Scala, and Infrastructure-as-Code tooling (Terraform / CloudFormation)
- Exceptional communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
Benefits
- Wellness programs that support the three pillars of your health – mental, physical, and financial
- The opportunity to move along a variety of career paths with amazing networking potential.
- Hybrid work arrangements as a condition of the role.
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