Overview
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 f
Full job description
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
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v2
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Ravl Io (lever) ↗Browse current Job and Scholarship listings from Ravl Io (lever) →
