Tirth Choksi

Machine Learning | Web3 | Software Engineer | Build In Public |
LinkedIn:

[Tirth Choksi @Tirth_dev22]

@VTikke do classical ML from this its pure gold, go for deep learning by goodfellow, alternatively you can explore https://t.co/VYWzZKV3rx for deep learning, this is what i am following rn

[Tirth Choksi @Tirth_dev22]

@divydoesnotcode 😂

[Tirth Choksi @Tirth_dev22]

Why don’t I have enoughhhh reachhhhh

[Tirth Choksi @Tirth_dev22]

Kya bhaiii log, kya bana rahe ho aaj kal projects me

[Tirth Choksi @Tirth_dev22]

@shirshakchavan Yess bro

[Tirth Choksi @Tirth_dev22]

@Abhijit_091 Right now, ChromaDB (obviously for vector embeddings), or else for relational databases, I would choose PostgreSQL.

[Tirth Choksi @Tirth_dev22]

@shirshakchavan @X Easiest growth hack is to get verified 🙂

[Tirth Choksi @Tirth_dev22]

Life Update: Starting Masters at @stonybrooku in Computer Science this fall..
Wish me luck guysss!!!!

[Tirth Choksi @Tirth_dev22]

@AvinashSingh_20 Heyy pls do mine
https://t.co/okLUc4GpVH

[Tirth Choksi @Tirth_dev22]

@kunal__23 Terko mile toh mera bhi le lena 😭😭

[Tirth Choksi @Tirth_dev22]

@raspberrychai_ Mah bro

[Tirth Choksi @Tirth_dev22]

@NoobSambit @AbhinavXJ @piyushgarg_dev 😂🤣🤣🤣

[Tirth Choksi @Tirth_dev22]

@thepoonam0914 I think we should ask what matter to AI that has been used by the recruiters 🙂😂😂

[Tirth Choksi @Tirth_dev22]

@SajalDhiman2 @claudeai I am more focused on the outcome part 👀

[Tirth Choksi @Tirth_dev22]

@pnxshy @maanas_tyagi Vaaaah vaaah kyaa uch vichaar hai aapke 😂

[Tirth Choksi @Tirth_dev22]

@_adityaa21 What about GenAI

[Suraj Sharma @suraj_sharma14]

As a Backend Engineer, you must build these projects.

Systems that prove you can scale, secure & ship.

1.) High-Throughput API Service
Build: FastAPI or Go service handling 10k+ RPS with async processing.
Why: Proves you understand concurrency, latency & load balancing.

2.) Real-Time Data Pipeline
Build: Kafka or Flink pipeline processing events with exactly-once semantics.
Why: Shows you can handle streaming data not just batch jobs.

3.) Vector Search Engine
Build: Similarity search over millions of embeddings with metadata filtering.
Why: Modern backends need semantic search not just keyword matching.

4.) Distributed Cache Layer
Build: Redis-based caching with invalidation strategies and cache warming.
Why: Database performance depends on your caching strategy.

5.) Multi-Tenant Auth System
Build: OAuth2/OIDC provider with RBAC, SSO & session management.
Why: Security is non-negotiable. You must understand identity deeply.

6.) Background Job Queue
Build: Celery or Bull alternative with retry logic, dead-letter queues, priorities.
Why: Async task processing is the backbone of scalable systems.

7.) Observability Platform
Build: Distributed tracing, structured logging, metrics dashboards, alerting.
Why: You cannot fix what you cannot see. Debugging at scale requires visibility.

8.) Event-Driven Microservices
Build: Pub/Sub architecture with saga pattern for distributed transactions.
Why: Monoliths do not scale. You need to manage service communication.

9.) Infrastructure as Code
Build: Terraform or Pulumi scripts provisioning entire environments reproducibly.
Why: Manual deployment is dead. Automation is mandatory.

10.) Database Sharding Strategy
Build: Horizontal partitioning with consistent hashing and rebalancing logic.
Why: Vertical scaling has limits. You must know how to scale data.

11.) Security Middleware
Build: Rate limiting, WAF rules, input validation, DDoS protection layers.
Why: One vulnerability can destroy trust. Security is a feature.

12.) CI/CD Pipeline
Build: GitHub Actions with automated testing, canary deployments, rollback.
Why: Shipping fast means shipping safely. Automation reduces risk.

13.) Real-Time WebSocket Server
Build: Bidirectional communication for chat, notifications or live updates.
Why: HTTP is not enough for modern interactive experiences.

14.) Cost Optimization Dashboard
Build: Track cloud spend per service, identify waste, automate resource scaling.
Why: Engineering decisions impact profitability. FinOps is part of the job.

15.) Disaster Recovery Plan
Build: Backup strategies, failover testing, data restoration procedures.
Why: Systems fail. Your ability to recover defines reliability.

Most people watch tutorials. Builders ship systems.

Bookmark & Repost.

[Suryansh Tiwari @Suryanshti777]

Most people want to become AI Engineers

Very few know what to learn next

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Follow me (so I can DM you)
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[Tirth Choksi @Tirth_dev22]

@Tech_girl At the end it’s all about your own intelligence, under the hood these are literally tools which are just automating stuff