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South Africa: Machine Learning Engineer (Intermediate) (Remote) posted by Datafin

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Job Description

Machine Learning Engineer (Intermediate) (Remote)Engineering/Technical
Remote

ENVIRONMENT:
Our client is on the hunt for an Intermediate Data Analyst / Machine Learning Engineer to grow their sim racing apps data driven telemetry analysis features. Youll turn raw laps into actionable insights – building data pipelines, training/evaluating ML.NET models, and shipping them into production. Youll work primarily in C#, Entity Framework Core (code-first) with MSSQL on the server and SQLite in the app, surfacing insights in their Blazor/WPF UI. Expect clear goals, fast feedback, and close collaboration with the CTO.
DUTIES:
  • Build end-to-end data features: ingest, clean, transform, and persist telemetry (laps, sectors, throttle/brake, steering, RPM, etc.)
  • Develop ML.NET models for driver coaching: lap alignment, pace deltas, consistency scoring, anomaly/outlier detection, stint/session segmentation
  • Move prototypes to production (batch and near-real-time inference) using C# + ML.NET
  • Implement backend services with EF Core (code-first)
    • Server: MSSQL (schema design, migrations, performance tuning)
    • App: SQLite (lightweight schemas, efficient queries, migrations)
  • Expose analytics via APIs and integrate results into Blazor/WPF dashboards and overlays
  • Add data quality checks, validation, and observability (metrics, logging, tracing)
  • Write integration tests, keep CI/CD green, and document datasets, features, and experiments
  • Participate in code reviews; follow and improve coding standards
REQUIREMENTS
  • 3+ years total experience, with solid C#/.NET backend skills
  • Practical ML.NET experience (regression/classification/clustering; time-series a plus)
  • Proficiency with EF Core, LINQ, and code-first workflows across MSSQL (server) and SQLite (app)
  • Ability to design features, evaluate models (cross-validation, proper metrics), and ship to production
  • Comfortable with Git workflows, integration testing, and CI/CD
Nice to have:
  • Signal processing for telemetry (resampling, smoothing, filtering)
  • Real-time/near-real-time analytics, caching, and background workers
  • Visualization skills for comparative laps and telemetry overlays
  • Experimentation (A/B), metric design (pace/consistency indices)
  • Interest in sim racing or motorsport
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