Machine Learning Engineer (Intermediate) (Remote)

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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