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We are looking for an ambitious, highly capable Full-Stack Software Engineer who leverages cutting-edge AI tools to multiply their productivity and own cloud features completely end-to-end, from initial design and architecture down to deployment, testing, and production support.

Were looking for cutting edge smart & capable engineers who can harness AI and can lead sophisticated projects from the requirement and design phases down to implementation, test and production delivery.

Key Responsibilities

End-to-End Feature Ownership: Own cloud features complete end-to-end, including backend services, frontend user interfaces, database schema design, automated testing, CI/CD deployment, and post-release support.
AI-Accelerated Development: Efficiently utilize advanced AI coding assistants and AI-driven workflows (e.g., Claude Code, Cursor, LLM-driven test generation) to design, code, debug, and deliver robust software at high velocity.
Frontend & Backend Engineering: Build and maintain scalable APIs and responsive, intuitive user interfaces (React, Go / Node.js).
Database & Infrastructure: Work with SQL/NoSQL databases and public cloud provider services to ensure high availability and optimal performance.
Quality & Automated Testing: Design, write, and execute comprehensive test suites (unit, integration, and E2E) to keep software stable and functional.
Production Support & Reliability: Participate in monitoring, troubleshooting, and supporting your delivered features in cloud environments.
Product & UX Collaboration: Work closely with Product and UX teams to rapidly turn concepts into seamless, user-friendly customer experiences.

Were looking for a Senior Backend Software Engineer to help develop our hyperscaling platform.
We have a lot of tasks on Golang and little less on Java and Python.

In this position, your responsibility will be to:
Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We are building an inference & fine-tuning platform that makes every kind of foundation model - text, vision, audio, and emerging multimodal architectures - fast, reliable, and effortless to train & deploy at massive scale.

Some directions we currently working on and which you can be a part of:
Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.
Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.



Some directions we are currently working on, and which you can be a part of:

Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We're an SRE team within DevTools, looking for someone ready to help maintain and grow our systems
Your responsibilities will include:

Improving services based on user feedback

Building fault-tolerant, self-healing architecture

Finding ways to speed up our systems and reduce user friction

Modifying well-known closed- and open-source solutions Supporting our users

we are looking for a Senior Site Reliability Engineer (SRE)
Your responsibilities will include:

Ensure fault-tolerance, scale, and uninterrupted operations for the service.
Use cutting-edge cloud technology to solve a variety of infrastructure problems.
Implement and improve CI/CD processes.
We expect you to have:

Solid experience with programming languages (like Go, Python, or C++);
Solid understanding of classic algorithms and data structures;
Commercial experience with and deep understanding of Unix systems and network technology;
Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm).

As a Senior Software Engineer on a search vertical, you'll help build systems that capture what is true about a domain. You'll work on extracting, connecting, retrieving, and reasoning over knowledge from the web and beyond, turning messy, real-world data into structured, trustworthy knowledge so AI agents can answer questions with precision and completeness.

You will optimize the retrieval and knowledge layer for a vertical: how a domain's content is indexed, linked into entities, ranked, and continuously refreshed, then measured and improved against rigorous IR metrics. This is an information-retrieval and systems role spanning indexing internals, hybrid retrieval, and entity resolution, with the goal of making each vertical the best place in the world to search its domain.

In this position, your responsibility will be to

Design, implement, and operate the retrieval system for a search vertical

Connect and tune the data pipeline, from ingestion to relevance tuning

Build knowledge-graph and entity-resolution layers: entity linking / NER, ontologies, and graph databases (Neo4j or similar)

Develop structured-extraction pipelines over messy, unstructured domain data

Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it

Define evaluation and quality metrics for relevance and drive measurable improvements

Collaborate with crawling, indexing, and ML teams to ensure retrieval and ranking requirements are met

Enable safe experimentation with retrieval, ranking, and extraction strategies

We are looking for an experienced and hands-on ATE Engineer to design, develop, and maintain the data and software infrastructure supporting our Automated Test Equipment (ATE) environments. In this role, you will establish the database architecture, data pipelines, reporting tools, and infrastructure required for electronic card testing, system-level testing, and radar calibration of advanced radar systems. Key Responsibilities:
* Design and maintain the ATE database and software infrastructure.
* Develop data pipelines, APIs, and integrations for ATE systems.
* Build BI dashboards and reports for production and test data.
* Ensure data integrity, traceability, backup, and availability.
* Support deployment across production sites and secured networks.
* Collaborate with ATE, Production, IT, Quality, and Cybersecurity teams.