Career Coaching Program · global
Coaching you can verify,
commit by commit
A selective, project-based coaching program: real engineering work with AI-assisted code review on your project work, a specialization track matched to your target role, and interview preparation that treats you like the professional you're becoming.
Open globally · advisors in the USA and India · request-based
Rather talk to a person first? An advisor can answer your questions and help you pick a track before you sign in to anything.
The arc
Four phases of project practice and interview preparation
PHASE 1
Foundations
Fill the gaps that interviews expose: fundamentals, tooling, and the discipline of daily committed work.
PHASE 2
Track depth
Your specialization track — real projects with AI-assisted code review on your project work, building a body of work you can show.
PHASE 3
Interview machine
Mock interviews, viva-style questioning, resume and profile work — until explaining your own code is second nature.
PHASE 4
Job-search guidance
Guidance on applications and positioning, with your project work as something you can choose to show.
Specialization tracks
Matched to the role you're targeting
You request a track based on your target role and current level, and an advisor confirms the fit with you. Each track is project-based and built around a target role. This list comes straight from the curriculum.
AI-Chip & ML-Systems Engineering (GPU Kernels to Compilers)
Build the layer that makes AI fast on hardware — the layer of the AI-infrastructure stack that sits closest to the hardware.
Related roles: GPU Kernel Engineer, ML Systems / Inference Engineer …
6 phases · 48 projects
AI / ML with Python
Build ML engineering skills through projects you can show and explain: data foundations (NumPy, pandas, viz, SQL), classical machine learning with honest evaluation, deep learning (CNNs, RNNs, transf…
Related roles: ML Engineer, Data Scientist …
6 phases · 49 projects
AI-Native / LLM Application Engineering
Build production LLM applications the way modern teams actually do: structured outputs, RAG, agents, tool use, evals, and MCP.
Related roles: AI Engineer, LLM Application Developer …
4 phases · 17 projects
Backend / API Engineering
Build production backends: REST and GraphQL APIs, relational and cached data, auth, background jobs, testing, and system design.
Related roles: Backend Engineer, API Engineer …
4 phases · 19 projects
Build Your Own Small Language Model
Build the whole stack that sits underneath a language model API, on the laptop you already own.
Related roles: Machine Learning Engineer (training and inference), LLM Infrastructure / Inference Engineer …
7 phases · 17 projects · 17 videos
C & Systems Programming (Zero to the Kernel)
Free startLearn C the way the systems world actually uses it — as the portable assembly that the Linux kernel, device drivers, embedded firmware, databases, and network stacks are written in.
Related roles: Systems / Kernel Engineer, Embedded / Firmware Engineer …
6 phases · 48 projects · 48 videos
Capital Markets Systems in C++ (OMS/EMS, FIX, Compliance & Settlement)
Learn how the software that runs the buy side and sell side actually works — by rebuilding it.
Related roles: Trading Systems Engineer (Buy-Side), OMS/EMS Platform Engineer …
6 phases · 48 projects
Computer Architecture & Systems (How the Machine Really Works)
Go beneath the language to the machine itself — the layer that separates a generic software engineer from a low-latency systems engineer.
Related roles: Low-Latency / HFT Engineer, AI-Chip / Kernel Engineer (foundation) …
6 phases · 48 projects
C++ From Zero (Absolute Beginner to Modern C++)
Learn C++ from the very first line of code to modern, idiomatic C++17/20 — the systems language that the shared core (data structures, computer architecture, performance) and the AI-chip branch are a…
Related roles: C++ Developer, Low-Latency / HFT Engineer (foundation) …
6 phases · 48 projects · 48 videos
DevOps / Cloud / Data Engineering
Operate and ship software at scale: Linux, containers, CI/CD, infrastructure-as-code, cloud, observability, and the data-engineering basics (pipelines, warehouses).
Related roles: DevOps Engineer, Cloud Engineer …
4 phases · 16 projects
Data Structures & Algorithms in C++ (Interview-Grade)
Turn your C++ fluency into problem-solving power.
Related roles: Software Engineer (technical interview preparation), Low-Latency / HFT Engineer (foundation) …
6 phases · 48 projects
Forward Deployed AI Engineering
Walk into a messy workflow.
Related roles: Forward Deployed AI Engineer, Applied AI Engineer (customer-facing) …
8 phases · 12 projects
Frontend Engineering
Modern frontend you can show and explain: from Git and HTML/CSS to JavaScript, TypeScript, React and Next.js, built through 90+ projects that become a live portfolio.
Related roles: Frontend Engineer, React Developer …
5 phases · 72 projects
Frontend Advanced — Next.js
Advanced, production-grade Next.js across eight phases and a deployable capstone: routing and the server/client boundary, forms and validation, data fetching with React Query, a reusable UI library,…
Related roles: Frontend Engineer, Next.js Developer …
8 phases · 88 projects
Full-Stack Engineering
Full-stack product engineering: build complete products end-to-end — frontend, backend, database, auth, and deployment — using Next.js full-stack.
Related roles: Full-Stack Engineer, Software Engineer …
4 phases · 16 projects
HFT & Low-Latency Engineering in C++
Engineer software where nanoseconds are money.
Related roles: Low-Latency C++ Engineer (HFT), Trading Systems Engineer …
6 phases · 48 projects
Math & Reasoning for Systems and Quant (Zero to Confident)
Build the mathematical spine that low-level and quantitative work relies on — from a true-zero start, learning by writing tiny programs that compute and verify each idea.
Related roles: Quant Trader (foundation), ML/AI-Systems Engineer (foundation) …
6 phases · 48 projects
Parallel Computing & Performance (CPU to GPU)
Make code fast by making it parallel.
Related roles: AI-Chip / GPU Kernel Engineer (foundation), HPC / Performance Engineer …
6 phases · 48 projects
Python Core (Beginner to Advanced)
Master the Python language end-to-end through projects: fundamentals, idiomatic and functional Python, object-oriented design, packaging and environments, the standard library, and concurrency, perfo…
Related roles: Python Developer, Software Engineer …
6 phases · 48 projects
Python Data Engineering & Automation
Build the pipelines and automation that power real systems with Python: scripting and CLI tools, web scraping and data acquisition, data engineering (ETL, validation, warehousing), big data and orche…
Related roles: Data Engineer, Automation Engineer …
5 phases · 43 projects
Python Web & Backend Engineering
Build production web backends and full-stack apps in Python: HTTP and ASGI foundations, REST APIs with FastAPI, databases and ORMs (SQLAlchemy, Django), authentication and security, async and real-ti…
Related roles: Backend Engineer (Python), Full-Stack Engineer (Python) …
6 phases · 45 projects
Quant Developer in Python: Research Infrastructure, Backtesting, Portfolio & Risk
Build the software a systematic research desk runs on, and be able to prove every number it prints.
Related roles: Quant Developer, Research Engineer (systematic trading) …
6 phases · 48 projects · 48 videos
Quant Trading — Mental Math, Probability & Market-Making
Practise the quantitative reasoning that trading interviews test.
Related roles: Quant Trader (Prop / HFT), Trading Intern / Junior Trader …
6 phases · 48 projects
Robotics & Humanoid Systems Engineering
Make C++ move in the physical world.
Related roles: Robotics Software Engineer, Humanoid / Controls Engineer …
6 phases · 48 projects
Enrollment & terms
One program, worldwide
The Career Coaching Program is a single global program. Wherever you are, you request a track the same way, build the same projects, and get the same coaching.
Program terms, fees, and payment details are confirmed in writing before enrollment, per your agreement — you'll know exactly what applies to you before you commit to anything. A track request is not an acceptance: an advisor reviews it.
Eligibility is open globally, with advisors based in the USA and India; work authorization for your target job market and program fit are confirmed during the advisor conversation.
Honest expectations
What this is not
- ✕ Not a video course — you build, and your project work gets reviewed
- ✕ Not a bootcamp certificate — the evidence is your own project work, which you choose whether to show
- ✕ Not a job placement service — we prepare you; employers hire you on merit
- ✕ Not for passive learners — half-effort produces half-results, and we say so up front
This program provides coaching, skill building, and job-search guidance. It does not guarantee employment, interviews, salaries, or any specific outcome — results depend on your effort, market conditions, and employer decisions.
TechMonster by the numbers
Live counts, not outcomes: we do not publish placements, hires, interviews or salaries. Counts under 10 are shown as “fewer than 10”.
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Requests open
Serious about the switch?
Sign in with GitHub, start the free first project, and request the track that fits your target role. If the fit is real, an advisor walks you through terms in writing — no surprises, no pressure. Questions first? Ask on WhatsApp.