Application Engineer

Synmatch AI; India; On-site; INR 800,000 - 1,200,000; Full time

Benefits offered by this job

Founding Influence

Specialist Team

Real Engineering Culture

Made-in-Germany Quality

Job summary

Join Synmatch AI as an Application Engineer focusing on measurement data processing. You will design the storage layout, ingest pipeline, and own mathematical core algorithms to ensure data integrity and operational efficiency.

As part of a founding engineering team, you will work alongside power-quality analysts and lead architects to develop innovative data solutions for a global provider of measurement instruments.

Benefits include a significant influence in shaping the product and collaborating with a dedicated team.

Qualifications

• Strong CS fundamentals including columnar layouts, compression, downsampling, and time-bucket indexing.
• Experience parsing large binary or text files in chunks without loading into memory.
• Strong in Dart, C, C++, or Rust with experience across FFI boundaries.

Responsibilities

• Define and evolve storage layout and ingestion layer.
• Build processing for event detection and analytical calculations.
• Share on-call rotation for data-plane incidents and lead postmortems.

Skills

Time-Series Data Structures

Streaming Ingest with Memory Discipline

Applied Math Implementation

Data Integrity as a Value

Domain Humility

Benchmark-First Instincts

Education

MSc in Electrical Engineering, applied mathematics, or related field

Tools

Dart

C

C++

Rust

Python

NumPy

Job description

How do you open a 2 GB waveform file on a tablet and let the user pan, zoom, and query it in milliseconds? That's the question this role exists to answer. Join Synmatch AI's client on the founding engineering team building the next generation of measurement analysis software for a global premium provider of measurement instruments. You'll design the storage layout, ingestion pipeline, and query patterns that everything else in the app depends on and keep that data plane healthy in production for years after you ship it.

In a power-quality analysis tool, a beautiful chart with the wrong number is worse than no chart at all. You'll own the mathematical core the algorithms that turn raw voltage and current samples into harmonics spectra, RMS values, flicker indices, sag/swell events, and standards-compliant aggregates. Recordings can span hours at tens of thousands of samples per second across multiple channels and phases. None of that is forgiving of "we'll optimize later."

You'll partner closely with an in-house power-quality analyst and measurement device engineers to translate measurement campaigns into precise on-device data contracts, and with the Lead Architect to ensure storage choices fit the broader system. You build it, you run it: when a customer's 4 GB recording opens slowly six months from now, you profile it, fix it, and write the regression test.

What you will do as an Application Engineer – Measurement Data Processing...

• Design On-Device Storage & Ingest Layer: Define and evolve storage (columnar layouts, compression schemes, downsampling pyramids, time-bucket indexes) and ingest layer (streaming, iterator-based parsing of large volumes in Dart with zero full-file slurps FFI to native code where it pays off)
• Implement Calculation Kernels: Build processing for event detection (sags, swells, transients), analytical calculations, and standards-compliant aggregations (e.g., IEC 61000-4‑x) choosing the right numerics for stability under long aggregation intervals
• Plan Schema Evolution & Cloud Sync: Forward- and backward-compatible migrations so customer files from year one still open in year five partial sync, vector clocks, conflict surfaces in close collaboration with Lead Architect
• Operate What You Ship: Share on-call rotation for data‑plane incidents, lead postmortems on ingest or query regressions, and turn each into permanent test or performance benchmark
• Validate Against Reference Vectors: Establish golden test vectors with PQ analyst, prototype in Python/NumPy, and prove production Dart/Rust kernels agree to required precision

What we are looking for…

• Time-Series Data Structures: Strong CS fundamentals columnar layouts, compression, downsampling, time-bucket indexing. Hands‑on with at least one embedded analytical engine (DuckDB, SQLite/drift, ClickHouse‑local, or equivalent)
• Streaming Ingest with Memory Discipline: Experience parsing large binary or text files in chunks without loading into memory. Comfortable with mmap, paged readers, and isolate‑based pipelines
• Applied Math Implementation: Strong in at least one of Dart, C, C++, or Rust; comfortable wiring kernels across FFI boundaries for complex numbers, Fourier analysis, Hilbert transforms, etc.
• Data Integrity as a Value: You consider silently losing a sample a critical bug, full stop
• Domain Humility: Willing to learn the physics before optimizing the bytes; comfortable working closely with a PQ analyst
• Benchmark-First Instincts: You measure before you tune, and write the harness yourself

Desirable (but not required):

• Experience with large data volumes using Apache Arrow, Parquet, or FlatBuffers especially with Dart FFI bindings
• Prior exposure to measurement, instrumentation, scientific software, or power-quality standards
• Python/NumPy/SciPy fluency for prototyping and reference computation
• MSc in Electrical Engineering, applied mathematics, or related field

Benefits and perks…

• Founding Influence: Contribute to the technical direction of a product defining a category for the next decade
• Specialist Team: Work alongside a dedicated power-quality analyst, visualization engineer, and hardware product teams
• Real Engineering Culture: ADRs, performance budgets, and reference test vectors are first-class artifacts
• Made-in-Germany Quality: Decades of measurement‑instrument heritage with a customer base that notices when the numbers are right