Tesla Machine Learning Engineer Interview Questions
Practice the exact questions companies are asking right now.

"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."

"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."

"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."

"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."

"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."

"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."

"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."

"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."

"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."

"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."

"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Implement 2D convolution forward pass
Problem Implement the forward pass of a 2D convolution (conv2d) from scratch (no deep learning libraries). You are given: - Input tensor x with shape ...
Implement attention and Transformer with backward pass
Implement Scaled Dot-Product Attention and a Transformer Block (No Autograd) Context: Build multi-head self-attention and a Transformer encoder-style ...
Compute Conv2D parameter counts
Parameter Count for a 2D Convolution Layer You are given a standard 2D convolution layer with: - Input channels: C_in - Output channels: C_out - Kerne...
Compare RNNs, LSTMs, Transformers, and MPC
Sequence Modeling Architectures and MPC (Technical Screen) You worked on a sequence-modeling project involving multivariate time-series signals and mu...
Implement automatic braking logic in Python
Using Python, implement a simple automatic braking function. Given current speed v (m/s), distance to obstacle d (m), maximum deceleration a_max (m/s^...
Explain and derive importance sampling estimators
Importance Sampling: Estimators, Properties, Optimal Proposals, and ESS Context You want to estimate an expectation under a target distribution p over...
Design an LLM math-solving chain
Design an LLM-Based Arithmetic Solver Context You are building an LLM-driven service that answers arithmetic questions ranging from simple expressions...
Model other agents in simulation
Scenario You are building a driving simulation environment for training/evaluating an autonomous agent (planning or RL). Besides the ego vehicle, the ...
Design RL reward for speed limits
RL Questions (conceptual + practical) You are training an RL agent for driving. Part A — Policy optimization - Explain the difference between PPO and ...
Compute suffix sums over waypoints
Problem You are given a batch of 2D waypoint trajectories. - Input: points with shape [B, N, 2], where points[b][i] = (x, y) is the i-th waypoint for ...
Implement and vectorize NumPy Conv2D
Implement a 2D convolution operation from scratch using NumPy only (no TensorFlow or PyTorch). Assume NCHW input shape (N, C_in, H_in, W_in) and weigh...
Compute nearest index within threshold after walking distances
You are given: ( 1) points: a list of N 2D coordinates in miles, points[i] = [x_i, y_i], ordered; ( 2) distances: a list of M nonnegative floats (mile...