Senior Research Scientist – Algorithms & Distributed Systems

Senior Research Scientist Algorithms & Distributed Systems

Team: YAL Advanced R&D Division

Location: Hyderabad

Type: Full-time Hands-on Applied Research

Compensation: Competitive (Aligned with top-tier engineering talent)

About YAL

YAL is building a secure, AI-native communication and discovery platform designed for hundreds of millions of users.

Our systems combine large-scale real-time messaging infrastructure with graph-based, relevance-driven discovery and ranking systems optimized for ultra-low latency, storage efficiency, privacy, and adversarial robustness.

This is foundational systems work.

We are not iterating on existing patterns we are designing next-generation infrastructure.

The Role

We are looking for an exceptional algorithmic thinker with deep distributed systems knowledge who can operate at competitive-programming level and translate theory into production-grade systems.

This is a hands-on applied research role. You will design novel algorithms, prototype them, benchmark them, and deploy them into real infrastructure.

You will work directly within the Advanced R&D division to define architectural standards across messaging, real-time systems, and discovery engines.

Core Responsibilities

1. Messaging & Distributed Systems

• Design scalable fan-out mechanisms for large groups (10k100k members).
• Develop efficient sharding strategies for billions of daily events.
• Implement offline-first synchronization (CRDTs, vector clocks, delta compression).
• Optimize distributed storage (tiered storage, compaction, indexing).
• Ensure sub-50ms read latencies under heavy load.

2. Real-Time Communication Infrastructure

• Design adaptive jitter buffer algorithms.
• Implement congestion control and bandwidth scheduling strategies.
• Optimize latency-sensitive streaming architectures.
• Evaluate and tune scalable codec pipelines.

3. Discovery & Recommendation Systems

• Build large-scale similarity search systems (ANN, HNSW, vector indexing).
• Design graph-based recommendation algorithms.
• Architect ranking models combining embeddings, graph signals, and trust signals.
• Develop distributed indexing strategies for billions of embeddings.

4. Research & Optimization

• Improve algorithmic complexity and constant-factor efficiency.
• Optimize memory layout and cache performance.
• Benchmark distributed systems under adversarial and peak loads.
• Publish internal RFCs defining architectural direction.

Bar for Excellence

We are not hiring routine engineers.

You should:

• Be deeply fluent in data structures, dynamic programming, graph algorithms, and optimization.
• Reason rigorously about time/space complexity.
• Understand distributed system trade-offs and failure modes.
• Be comfortable implementing high-performance systems in C++ / Rust / Go / Java.
• Move seamlessly from theoretical modeling to production deployment.
• Enjoy solving hard problems under constraint.

Competitive programming background (ICPC/IOI/Codeforces-level) is strongly valued but not mandatory if equivalent depth is demonstrated.

Required Expertise

• Advanced data structures & algorithms
• Distributed systems design
• Storage engines & indexing
• Vector search & approximate nearest neighbors
• Graph modeling & ranking systems
• Performance profiling & optimization
• Real-time systems fundamentals

What Success Looks Like

Within 3 months:

• You deliver a prototype improving latency, synchronization efficiency, or discovery quality.
• Your benchmarks influence architectural decisions.
• Your RFCs become reference documents for implementation teams.
• Your work directly powers large-scale production systems.

Why Join YAL

• Rare opportunity to design large-scale communication + discovery infrastructure together.
• Applied research that directly ships to users.
• Work on problems at internet scale from day one.
• High ownership and technical autonomy.
• Competitive compensation.