Principal Machine Learning Engineer

Principal Machine Learning Engineer

- (Hybrid, 3 days/week in-office)

About the Role:

We are seeking an exceptional Principal Machine Learning Engineer to provide technical and inspirational leadership to our world-class Data and AI team. This is a business-critical role that will be instrumental in shaping the future of our Intelligent Data division. Our team is at the forefront of building groundbreaking, real-time AI applications that solve complex, high-impact problems. Our work is distinguished by its sophistication and our ability to build robust, high-quality data platforms where governance and management are paramount.

Key examples of our work include:

• Real-time Fraud Prevention: For a major bank, we engineered a system that ingests diverse behavioural and financial data to not only detect but prevent fraud by blocking suspicious transactions in the moment they occur.
• Advanced Vehicle Telemetry: We developed a solution to model and process real-time event data from in-vehicle devices, dramatically reducing false alarms for hijackings and improving response times. With over five years of production experience with Large Language Models (LLMs)— including being one of the first to fine-tune a GPT-3 model in 2020—we operate a highly advanced data science and engineering practice.

The successful candidate will not only contribute to these projects but will also help define our ML strategy, inspire the team with a compelling vision, and represent us as a public thought leader.

Key Responsibilities:

This is a multi-faceted "jack-of-all-trades, master of machine learning" position.
The ideal candidate is fundamentally a top-tier engineer who builds the entire application ecosystem that supports AI, not a data scientist who exclusively builds models.

Technical & Architectural Leadership:

• Serve as the lead technical authority and consultant for team leads on the design and architecture of complex, real-time, scalable, and maintainable AI/ML systems.
• Lead the resolution of the most complex technical challenges, making key decisions that impact the overall architecture.
• Provide expert guidance on data streaming technologies and event-driven architectures, which are critical to our work.
• Evaluate and champion new technologies, tools, and frameworks to keep our practice at the cutting edge. Strategic Contribution:
• Work directly with leadership to define, refine, and execute the division's overall machine learning strategy.
• Stay at the forefront of industry trends, researching and applying knowledge of emerging technologies (e.g., LLMs, Generative AI, AI Personal Assistants) to drive innovation and maintain our competitive edge.

Team Leadership & Mentorship
:

• Inspire, coach, train, and mentor the data team, elevating their collective skill set and guiding them toward our new technical vision.
• Foster a culture of technical excellence, collaboration, and continuous learning.
• Conduct thorough code reviews and advocate for the highest standards of quality assurance.

Thought Leadership & Communication:

• Act as a key voice and evangelist for the Intelligent Data team, both internally and externally.
• This individual must be an effective and confident communicator, comfortable with public speaking, presenting at conferences, and creating compelling content (e.g., blog posts, social media, videos).

Skills:

• We are searching for a rare talent and acknowledge that this individual is likely in high demand. We are looking for an inspiring, dynamic, and technically brilliant leader.

Non-Negotiable Requirements:

• A Machine Learning Engineer at Heart:
  Must have a proven track record of engineering and building the end-to-end applications and ecosystems that support AI.
• Data Streaming & Platform Expertise: Deep, hands-on experience with data streaming technologies (e.g., Kafka, Flink) and a comprehensive understanding of modern data platforms are absolutely essential.
• Multi-Cloud Mastery: Extensive experience architecting and building solutions across different cloud environments.

The order of preference and expertise is

1. AWS,

2. GCP,

3. Azure.

Technical Versatility:

Deep knowledge of multiple programming languages (e.g., Python, Go, Java, C#) and their ecosystems.

Inspirational Leadership & Influence:

Must be a dynamic and inspiring individual with proven experience mentoring, coaching, and leading high-performing technical teams.

Exceptional Communication:

Must be able to articulate complex technical concepts clearly to both technical and non-technical stakeholders.
A demonstrated history of thought leadership (conference talks, publications, etc.) is highly desirable.

Technologies & Concepts

• Cloud Platforms - AWS (Primary), GCP, Azure. Deep knowledge of services like Lambda, S3, RDS, DynamoDB, VPC, etc. is expected.
• Data Streaming - Kafka, Flink, Beam
• Programming Languages - Python, Go, Java, C#, JavaScript
• Architecture - Microservices, Event-Driven Architecture, Kubernetes, Docker
• Data & ML - Experience with both structured and unstructured data, semi-supervised learning, Jupyter Notebooks, SageMaker.
• Databases - SQL (e.g., MS SQL, MySQL), NoSQL (e.g., Mongo), Graph (e.g., Neo4J)
• Process - Agile methodologies (Scrum, Kanban)