Get a High-Paying Tech Job

Software engineers like you join Outcome School to achieve the outcome that is a high-paying tech job.

Transition to
AI EngineerAI Agent EngineerHarness EngineerVoice AI EngineerAI ArchitectLLM EngineerLLM Inference EngineerGen AI EngineerMLOps EngineerForward Deployed EngineerML EngineerDeep Learning EngineerStaff EngineerSenior Software EngineerTeam LeadPrincipal Engineer

Designed for Outcome

Programs to help developers get a high-paying job by learning the internals of how things work and mastering system design.

Recorded Classes

Self-paced recorded classes for AI and ML, and Android. Simple explanations for complex topics.

Two Programs

You can choose from "AI and Machine Learning" or "Android".

Learn from Anywhere

As this program is completely online, you can join it from anywhere in the world.

We teach Internals

To get a high-paying tech job, you must know the internals and be great at system design. Knowledge comes to those who crave for it.

Eligibility

Working professionals - anyone already working in tech but looking for a high-paying tech job by learning the internals and System Design.

Your Teacher

Amit Shekhar

Founder @ Outcome School • IIT 2010-14 • I have taught and mentored many developers, and their efforts landed them high-paying tech jobs, helped many tech companies in solving their unique problems, and created many open-source libraries being used by top companies. I am passionate about sharing knowledge through open-source, blogs, and videos.

Amit Shekhar

Our Students' Growth

Got Salary Hike

CTC Change: 4 LPA → 24 LPA, 9 LPA → 24 LPA, 13 LPA → 46 LPA, 20 LPA → 60 LPA

Notable Transition

Software Engineer → VP of Engineering, Software Engineer → Staff Engineer

Open Source

Worked on Open Source projects and received interview calls from Top Companies

Our students got placed in top companies thanks to their efforts.

Meta
Google
Uber
Microsoft
Gojek
Deliveroo
Walmart
JPMorgan
Coupang
Flipkart
Swiggy
PayTM
NoBroker
Boeing
Target
DP World
Tesco
Chalo
Ixigo
Meesho
Samsung
Expedia
OLX
Upstox
Allen Digital
Motive
…and many more

What students are saying about us

Kiran Rao Chavan

Kiran Rao Chavan

Hi Amit, with every class that I see and hear from you, silently learning the techniques of system design skills in developing AI from scratch is phenomenal and I was impressed with "Attention is all you need" Paper explanation was next level. I have read YOLO Paper for image processing and writing python scripts after multiple attempts, but the way you give real time examples and the analogies that you give while explaining toughest things - you make it look like a cake walk. KVCache, Paged Attention, vLLM, Quantization, each and every concept that you teach is exceptional.

Aman Shekhar

Aman Shekhar

Outcome School delivers deep, practical AI/ML mastery that standard degree programs simply cannot match. Under Amit’s expert supervision, the curriculum shifts you from an AI consumer to an AI builder, instead of just using tools like Claude, you build autonomous AI agents, build LLMs from scratch, playing with KVCache, code Transformer architectures line by line etc. The best part was understanding the paper "Attention is all you need", not only that now I can read and understand any whitepaper. This rigorous, code-first approach has completely transformed my career trajectory, elevating me to the official AI Focal Point in my organization and the go-to expert for all complex technical queries.

Khush Panchal

Khush Panchal

Amit has been an incredible mentor to me. Under his guidance, I navigated the world of open source, which took my journey to the next level. Amit's presence works as a catalyst in the journey of learning and growing. His insights were incredibly helpful, whether it was cracking firms like Microsoft and Blinkit, negotiating salaries, or making career decisions. His mentorship also enabled me to create major open-source libraries. I am grateful to have Amit as a lifelong mentor and look forward to creating a positive impact with him.

Ready to get a high-paying tech job?

Explore our programs.

Recent Blogs

We publish high-quality blogs regularly for our learners.

Do you need a degree or advanced math to become an AI Engineer?

Do you need a degree or advanced math to become an AI Engineer?

No, you do not need a degree or advanced math to become an AI Engineer, because the job is about building products on top of existing models with a coding agent, and the math it uses is a small set that anyone can learn in a few weeks.

What are audio frames and chunk sizes in a real-time voice pipeline?

What are audio frames and chunk sizes in a real-time voice pipeline?

An audio frame is a small, fixed slice of sound, usually 10 or 20 milliseconds long, and the chunk size is how much of that sound we pass from one step of a voice pipeline to the next at one time.

How does Prompt Engineering work?

How does Prompt Engineering work?

Prompt Engineering is the skill of writing clear and well-structured prompts, the instructions we give an AI model, so that the model gives us the exact output we want.

What is RLAIF? Reinforcement Learning from AI Feedback Explained

What is RLAIF? Reinforcement Learning from AI Feedback Explained

RLAIF (Reinforcement Learning from AI Feedback) is a way to train an LLM where another AI model, and not a human, decides which of two answers is better. These AI decisions are then used to teach the LLM to give better answers.

What is Reinforcement Learning with Verifiable Rewards (RLVR)?

What is Reinforcement Learning with Verifiable Rewards (RLVR)?

Reinforcement Learning with Verifiable Rewards (RLVR) is a way to train an LLM where a program checks the model's final answer and gives a reward of 1 if it is correct and 0 if it is wrong. The model then learns to produce more of the answers that got 1.

How does a voice agent add its own backchannels like "okay" and "got it"?

How does a voice agent add its own backchannels like "okay" and "got it"?

A voice agent adds its own backchannels like "okay" and "got it" by running a fast, separate system next to the main conversation, which predicts the short moments where a listener would say "mm-hmm" and plays a short pre-recorded sound without taking the turn. It also says a quick "got it" right after the user finishes, so that the user knows they were heard while the real answer is still being prepared.