Principal Platform Engineer, Machine Learning

RAVL is a boutique technology advisory and engineering firm focused on the financial services industry. Everything we do is centered on helping our clients realize measurable ROI from their technology investments.

We’re growing our engineering team and hiring ML Platform Engineers to design and build scalable machine learning platforms across clients. This includes developing cloud-native ML infrastructure, enabling MLOps capabilities, and supporting end-to-end model lifecycle management in enterprise environments.

These roles include both immediate project needs and pipeline hiring for upcoming engagements, with a focus on building reliable, production-grade ML systems at scale.

Architect and lead development of ML platforms on Azure Databricks

Design systems for training, feature engineering, model serving, and monitoring

Build and standardize MLOps pipelines (CI/CD for ML, model versioning, deployment workflows)

Extend Databricks with custom services, APIs, and integrations

Integrate with enterprise systems (IAM, secrets, observability, governance)

Optimize performance, scalability, and cost efficiency of ML workloads

Define platform standards and engineering best practices

Mentor engineers and guide technical direction

Deep experience building ML or data platforms at scale

Strong expertise with Azure + Databricks (Spark, MLflow, jobs, clusters)

Experience with MLOps tooling and model lifecycle management

Strong backend engineering (Python/Scala/Java)

Experience with distributed systems and data processing

Familiarity with enterprise integrations (identity, security, observability)

Kubernetes and containerized ML workloads

Feature stores and real-time inference systems

Platform-first and systems-oriented

Strong ownership and technical leadership

Pragmatic with a focus on scalability

Flexible, client-aligned work model — autonomy with accountability, adapting to client delivery needs

Variable bonus & RRSP contributions tied to performance and delivery impact.

4 weeks paid time off (plus public holidays)

Paid professional development days and continuous learning opportunities

Comprehensive health & dental coverage, including mental health support

Commitment to lifelong learning — continuous improvement through training, mentorship, and certification