Description review
Location: Istanbul, Türkiye Remote: Yes
Location: Istanbul, Türkiye Remote: Yes · Remote · back to the listing
HR standards
44/100
poor
Title ↔ description
19/100
poor
Reads as
Unclear
no confident match
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Willing to relocate: Yes
Technologies: C/C++, Rust, Python, Linux, RTOS, TCP/IP, eBPF/XDP, WebRTC, UWB/BLE, embedded/IoT & mesh-connected devices, PostgreSQL, Docker, AI/LLM systems
Résumé / Portfolio: https://msakg.com GitHub: https://github.com/imsakg LinkedIn: https://linkedin.com/in/msakg Email: [email protected]
Lead AI Agent Software Engineer focused on real-time, performance-critical systems across AI, networking, embedded devices, and production infrastructure.
My background sits at the intersection of software and the physical world:
• Currently leading architecture and production hardening of a real-time multimodal AI agent platform — streaming STT → LLM/tools → TTS, WebRTC, asyncio, long-lived state/memory, retrieval, observability, failure handling, cancellation, backpressure, and latency-sensitive execution.
• Previously built real-time networking software for aerial systems using Rust, Linux, eBPF/XDP and IEEE 802.1 TSN concepts, including reliability mechanisms where deterministic behavior and low fast-path overhead matter.
• Earlier developed C/C++ bare-metal and RTOS firmware for access-control/security and embedded/IoT devices — TCP/IP, UART/I2C/SPI, RS232/RS485, Modbus, secure device communication, UWB/BLE localization, sensors, relays and constrained hardware.
I’m most interested in difficult engineering problems where timing, reliability, networking, hardware constraints, and user-facing behavior meet: mission/performance-critical software, real-time systems, embedded/IoT, access control, UWB, distributed device systems, AI infrastructure, backend/platform engineering, and systems software.
I enjoy owning systems end-to-end — architecture, implementation, debugging, benchmarking, deployment, production incidents, and the less glamorous failure modes that only appear in real environments.
I’m looking for a strong engineering team tackling genuinely hard technical problems. Open to Lead/Senior Software, Systems, Embedded, Platform, Backend, Real-Time AI, or similarly hands-on engineering roles.
If you're building something where milliseconds, reliability, hardware, networks, or production correctness actually matter, I'd be very happy to talk.
Technologies: C/C++, Rust, Python, Linux, RTOS, TCP/IP, eBPF/XDP, WebRTC, UWB/BLE, embedded/IoT & mesh-connected devices, PostgreSQL, Docker, AI/LLM systems
Résumé / Portfolio: https://msakg.com GitHub: https://github.com/imsakg LinkedIn: https://linkedin.com/in/msakg Email: [email protected]
Lead AI Agent Software Engineer focused on real-time, performance-critical systems across AI, networking, embedded devices, and production infrastructure.
My background sits at the intersection of software and the physical world:
• Currently leading architecture and production hardening of a real-time multimodal AI agent platform — streaming STT → LLM/tools → TTS, WebRTC, asyncio, long-lived state/memory, retrieval, observability, failure handling, cancellation, backpressure, and latency-sensitive execution.
• Previously built real-time networking software for aerial systems using Rust, Linux, eBPF/XDP and IEEE 802.1 TSN concepts, including reliability mechanisms where deterministic behavior and low fast-path overhead matter.
• Earlier developed C/C++ bare-metal and RTOS firmware for access-control/security and embedded/IoT devices — TCP/IP, UART/I2C/SPI, RS232/RS485, Modbus, secure device communication, UWB/BLE localization, sensors, relays and constrained hardware.
I’m most interested in difficult engineering problems where timing, reliability, networking, hardware constraints, and user-facing behavior meet: mission/performance-critical software, real-time systems, embedded/IoT, access control, UWB, distributed device systems, AI infrastructure, backend/platform engineering, and systems software.
I enjoy owning systems end-to-end — architecture, implementation, debugging, benchmarking, deployment, production incidents, and the less glamorous failure modes that only appear in real environments.
I’m looking for a strong engineering team tackling genuinely hard technical problems. Open to Lead/Senior Software, Systems, Embedded, Platform, Backend, Real-Time AI, or similarly hands-on engineering roles.
If you're building something where milliseconds, reliability, hardware, networks, or production correctness actually matter, I'd be very happy to talk.