u/IcyHomework6605

I’m looking for some honest, blunt advice from recruiters, hiring managers, senior engineers, or people who have successfully landed AI/ML roles in the US market.
I’m currently job hunting for AI/ML Engineer, Machine Learning Engineer, and Generative AI/Agentic AI roles.
The confusing part is that I am getting recruiter attention, but I’m repeatedly getting rejected after screening/interview stages.
Over the past few months, I’ve received screening/interview opportunities with companies including EY, Ford, TikTok, Nimble Gravity, Goldman Sachs, Capital One, and several others.
So I don’t think my biggest problem is getting my resume noticed.
The problem is converting those opportunities into the next round or an offer.
For example, with Goldman Sachs, I went through their coding process. I passed the coding-related stages, solved the problems, and explained my approach and code during the interview. I still ended up receiving a rejection.
I’ve had similar experiences with other companies where I felt the recruiter/screening conversation went reasonably well, but I was rejected afterward.
At this point, I’m trying to identify whether there is a recurring problem in my interviewing that I’m not recognizing myself.
I would really appreciate advice on:
What are recruiters actually evaluating during an initial screening?
If my technical answers are correct, what else could cause a rejection?
How important is communication during technical interviews?
How do I know if I’m giving answers that are too long, too technical, or not detailed enough?
For AI/ML/GenAI roles, what do hiring managers actually want to hear when discussing previous projects?
How important is it to clearly explain what I personally built versus what the overall team built?
If I solve a coding problem correctly and explain my solution, what could still cause a rejection?
Could my resume be creating expectations about my experience that I’m not demonstrating effectively during interviews?
How should I talk about experience with LLMs, RAG, Agentic AI, LangChain/LangGraph, AWS Bedrock/Azure OpenAI, and production ML systems without either underselling myself or exaggerating?
What are some common interview mistakes that candidates don’t realize they’re making?
I’m not looking for generic advice like “keep applying,” “network more,” or “don’t give up.” I’m already doing that.
I’m specifically trying to understand what I need to change in my interview performance.
If you’re a recruiter, hiring manager, senior engineer, or someone who regularly interviews candidates, I would genuinely appreciate blunt and constructive feedback.
If you were in my position, what would you change first?
I’m taking my job search seriously and I’m completely open to criticism. I’d rather hear what I’m doing wrong than receive generic encouragement.
Thanks in advance.

I’m looking for some honest, blunt advice from recruiters, hiring managers, senior engineers, or people who have successfully landed AI/ML roles in the US market.
I’m currently job hunting for AI/ML Engineer, Machine Learning Engineer, and Generative AI/Agentic AI roles.
The confusing part is that I am getting recruiter attention, but I’m repeatedly getting rejected after screening/interview stages.
Over the past few months, I’ve received screening/interview opportunities with companies including EY, Ford, TikTok, Nimble Gravity, Goldman Sachs, Capital One, and several others.
So I don’t think my biggest problem is getting my resume noticed.
The problem is converting those opportunities into the next round or an offer.
For example, with Goldman Sachs, I went through their coding process. I passed the coding-related stages, solved the problems, and explained my approach and code during the interview. I still ended up receiving a rejection.
I’ve had similar experiences with other companies where I felt the recruiter/screening conversation went reasonably well, but I was rejected afterward.
At this point, I’m trying to identify whether there is a recurring problem in my interviewing that I’m not recognizing myself.
I would really appreciate advice on:
What are recruiters actually evaluating during an initial screening?
If my technical answers are correct, what else could cause a rejection?
How important is communication during technical interviews?
How do I know if I’m giving answers that are too long, too technical, or not detailed enough?
For AI/ML/GenAI roles, what do hiring managers actually want to hear when discussing previous projects?
How important is it to clearly explain what I personally built versus what the overall team built?
If I solve a coding problem correctly and explain my solution, what could still cause a rejection?
Could my resume be creating expectations about my experience that I’m not demonstrating effectively during interviews?
How should I talk about experience with LLMs, RAG, Agentic AI, LangChain/LangGraph, AWS Bedrock/Azure OpenAI, and production ML systems without either underselling myself or exaggerating?
What are some common interview mistakes that candidates don’t realize they’re making?
I’m not looking for generic advice like “keep applying,” “network more,” or “don’t give up.” I’m already doing that.
I’m specifically trying to understand what I need to change in my interview performance.
If you’re a recruiter, hiring manager, senior engineer, or someone who regularly interviews candidates, I would genuinely appreciate blunt and constructive feedback.
If you were in my position, what would you change first?
I’m taking my job search seriously and I’m completely open to criticism. I’d rather hear what I’m doing wrong than receive generic encouragement.
Thanks in advance.

I’m looking for some honest advice from experienced hiring managers, recruiters, senior engineers, or people who have successfully navigated the US tech job market.
I’m currently job hunting for AI/ML / Generative AI / Machine Learning Engineer roles, and I’m struggling to understand what I’m doing wrong during the interview process.
My resume has been getting recruiter attention, and I’ve received screening calls from companies including:
EY
Ford
TikTok
Nimble Gravity
Goldman Sachs
Capital One
and several others
So I don’t think the biggest problem is getting my resume noticed.
The problem is what happens after that.
I’ve had multiple recruiter/screening conversations where I felt the conversation went reasonably well, but I eventually received a rejection.
The most frustrating example was Goldman Sachs. I made it through their coding process, completed the coding interview, solved the problems, and explained my approach/code clearly during the interview. Despite that, I ultimately received a rejection.
I’ve also had a coding/interview process with Capital One.
At this point, I’m trying to figure out whether there is a recurring problem in my interviewing that I’m not recognizing myself.
What I want to understand
For people who interview candidates or have gone through these processes successfully:
What are recruiters actually evaluating during an initial screening call?
If I answer the technical questions correctly, what other things can cause a recruiter/hiring manager to reject me?
How important are communication skills during a technical screening?
How can I tell whether I’m giving answers that are too long, too technical, or not detailed enough?
For AI/ML/GenAI roles, what do hiring managers actually want to hear when they ask about previous projects?
How much does demonstrating personal ownership matter? For example, explaining exactly what I built versus describing the overall team/project.
If I pass a coding interview and explain my solution well but still get rejected, what are the most common reasons?
Could my resume be creating expectations that I’m not successfully demonstrating during interviews?
How should I answer questions about my years of experience with things like LLMs, RAG, Agentic AI, LangChain/LangGraph, AWS Bedrock/Azure OpenAI, and production ML systems without either underselling myself or exaggerating?
What are the biggest mistakes you see candidates make during recruiter screens that candidates themselves usually don’t realize?
What I DON’T want
I’m not looking for generic advice like:
“Keep applying”
“Network more”
“Improve your resume”
“Don’t give up”
I’m already doing those things.
I’m looking for specific, critical feedback about the interview stage and what might be causing the repeated rejections.
I’m also willing to accept that the problem could be my communication, technical depth, experience level, interview answers, or something else I’m completely unaware of.
If you’re a recruiter, hiring manager, senior engineer, or someone who has interviewed many candidates for AI/ML roles, what would you look for in my situation and what would you change first?
I’m taking the job search very seriously right now, so I’d genuinely appreciate blunt feedback rather than encouragement.
Thank you.

Hi everyone,
I have a **60-minute Zoom phone interview** coming up for the **Associate Delivery Consultant, AI/ML (AWS Professional Services)** role, and I’m trying to understand what to expect.
A few details:
It’s a Zoom interview with one interviewer.
The role is customer-facing within AWS Professional Services.
My background is in AI/ML with around 4 years of software engineering experience, including Python, LLMs, RAG, LangChain, AWS, and deploying AI applications.
I’m curious about a few things:
Is this first interview mainly behavioral, technical, or a mix of both?
How deep do they go into AWS services like Bedrock, SageMaker, Lambda, IAM, S3, etc.?
Should I expect coding (e.g., LeetCode-style), system design, or more architecture and solution discussion?
Which Amazon Leadership Principles came up the most in your interview?
How customer-focused is the interview? Do they ask consulting or client communication scenarios?
Any specific AI/ML topics I should prioritize (RAG, LLMs, vector databases, prompt engineering, MLOps, etc.)?
Any advice on what helped you succeed or what you wish you’d prepared better?
I’d really appreciate hearing from anyone who has interviewed for this role or a similar AWS ProServe position. Thanks in advance!

Hi everyone,
I have a 60-minute Zoom phone interview coming up for the Associate Delivery Consultant, AI/ML (AWS Professional Services) role, and I’m trying to understand what to expect.
A few details:
It’s a Zoom interview with one interviewer.
The role is customer-facing within AWS Professional Services.
My background is in AI/ML with around 4 years of software engineering experience, including Python, LLMs, RAG, LangChain, AWS, and deploying AI applications.
I’m curious about a few things:
Is this first interview mainly behavioral, technical, or a mix of both?
How deep do they go into AWS services like Bedrock, SageMaker, Lambda, IAM, S3, etc.?
Should I expect coding (e.g., LeetCode-style), system design, or more architecture and solution discussion?
Which Amazon Leadership Principles came up the most in your interview?
How customer-focused is the interview? Do they ask consulting or client communication scenarios?
Any specific AI/ML topics I should prioritize (RAG, LLMs, vector databases, prompt engineering, MLOps, etc.)?
Any advice on what helped you succeed or what you wish you’d prepared better?
I’d really appreciate hearing from anyone who has interviewed for this role or a similar AWS ProServe position. Thanks in advance!

Hi everyone,
I have a 60-minute Zoom phone interview coming up for the Associate Delivery Consultant, AI/ML (AWS Professional Services) role, and I’m trying to understand what to expect.
A few details:
It’s a Zoom interview with one interviewer.
The role is customer-facing within AWS Professional Services.
My background is in AI/ML with around 4 years of software engineering experience, including Python, LLMs, RAG, LangChain, AWS, and deploying AI applications.
I’m curious about a few things:
Is this first interview mainly behavioral, technical, or a mix of both?
How deep do they go into AWS services like Bedrock, SageMaker, Lambda, IAM, S3, etc.?
Should I expect coding (e.g., LeetCode-style), system design, or more architecture and solution discussion?
Which Amazon Leadership Principles came up the most in your interview?
How customer-focused is the interview? Do they ask consulting or client communication scenarios?
Any specific AI/ML topics I should prioritize (RAG, LLMs, vector databases, prompt engineering, MLOps, etc.)?
Any advice on what helped you succeed or what you wish you’d prepared better?
I’d really appreciate hearing from anyone who has interviewed for this role or a similar AWS ProServe position. Thanks in advance!

Hey everyone. I’ve never really been a reader, but I’m at a point in life where I want to change that. I’m going through a pretty intense job search and interview season, and I’ve noticed my communication and confidence under pressure could use work. I also just want to build a genuine reading habit for the first time.

Looking for recommendations that are:

\*\*•\*\*	Easy to get into for a first-time reader (short chapters, engaging, not too dense)    
\*\*•\*\*	Useful for communication skills, confidence, or negotiation    
\*\*•\*\*	Bonus if it also helps with focus/productivity habits

Thanks in advance!

Hey everyone. I’ve never really been a reader, but I’m at a point in life where I want to change that. I’m going through a pretty intense job search and interview season, and I’ve noticed my communication and confidence under pressure could use work. I also just want to build a genuine reading habit for the first time.

Looking for recommendations that are:

**•**	Easy to get into for a first-time reader (short chapters, engaging, not too dense)  
**•**	Useful for communication skills, confidence, or negotiation  
**•**	Bonus if it also helps with focus/productivity habits

Thanks in advance!

Hey everyone. I’ve never really been a reader, but I’m at a point in life where I want to change that. I’m going through a pretty intense job search and interview season, and I’ve noticed my communication and confidence under pressure could use work. I also just want to build a genuine reading habit for the first time.

Looking for recommendations that are:

**•**	Easy to get into for a first-time reader (short chapters, engaging, not too dense)  
**•**	Useful for communication skills, confidence, or negotiation  
**•**	Bonus if it also helps with focus/productivity habits

Thanks in advance!

Hi everyone,
I recently completed my recruiter phone screen for a Software Engineer position on the Google Cloud AI team, and my recruiter explained the overall interview process.
From what I understand, the process is:
2 virtual interviews:
1 Coding
1 Googliness / Leadership
If those go well:
AI Depth interview
Another coding interview (currently planned as onsite)
I’d love to hear from people who have recently gone through this process.
Some questions I have:
How difficult were the first two virtual interviews compared to the final interviews?
What was your coding interview experience like? Were the questions closer to LeetCode Medium or Hard?
For the AI Depth interview, how deeply did they dive into your projects? Was it mostly resume-based, system design, or theory?
How was the onsite experience? Were the interviewers noticeably different from the virtual rounds?
Did anyone have their final rounds conducted virtually instead of onsite?
Looking back, what do you wish you had prepared more for?
Any tips that helped you succeed or things you wish you had known beforehand?
I’d really appreciate hearing about your experience, especially if you’ve interviewed for Google Cloud AI or another AI/ML Software Engineer role recently.
Thanks!

Hi everyone,
I recently completed my recruiter phone screen for a Software Engineer position on the Google Cloud AI team, and my recruiter explained the overall interview process.
From what I understand, the process is:
2 virtual interviews:
1 Coding
1 Googliness / Leadership
If those go well:
AI Depth interview
Another coding interview (currently planned as onsite)
I’d love to hear from people who have recently gone through this process.
Some questions I have:
How difficult were the first two virtual interviews compared to the final interviews?
What was your coding interview experience like? Were the questions closer to LeetCode Medium or Hard?
For the AI Depth interview, how deeply did they dive into your projects? Was it mostly resume-based, system design, or theory?
How was the onsite experience? Were the interviewers noticeably different from the virtual rounds?
Did anyone have their final rounds conducted virtually instead of onsite?
Looking back, what do you wish you had prepared more for?
Any tips that helped you succeed or things you wish you had known beforehand?
I’d really appreciate hearing about your experience, especially if you’ve interviewed for Google Cloud AI or another AI/ML Software Engineer role recently.
Thanks!

Hi everyone,
I recently completed my recruiter phone screen for a Software Engineer position on the Google Cloud AI team, and my recruiter explained the overall interview process.
From what I understand, the process is:
2 virtual interviews:
1 Coding
1 Googliness / Leadership
If those go well:
AI Depth interview
Another coding interview (currently planned as onsite)
I’d love to hear from people who have recently gone through this process.
Some questions I have:
How difficult were the first two virtual interviews compared to the final interviews?
What was your coding interview experience like? Were the questions closer to LeetCode Medium or Hard?
For the AI Depth interview, how deeply did they dive into your projects? Was it mostly resume-based, system design, or theory?
How was the onsite experience? Were the interviewers noticeably different from the virtual rounds?
Did anyone have their final rounds conducted virtually instead of onsite?
Looking back, what do you wish you had prepared more for?
Any tips that helped you succeed or things you wish you had known beforehand?
I’d really appreciate hearing about your experience, especially if you’ve interviewed for Google Cloud AI or another AI/ML Software Engineer role recently.

Thanks !

I’m actively looking for AI/ML Engineer opportunities in the U.S. job market and would appreciate some advice from the community.
Background:
• 3+ years of industry experience in AI/ML
• Production ML systems in financial services and healthcare
• Experience with LLMs, RAG, LangChain, LangGraph, Agentic AI, MLOps, AWS, PyTorch, NLP, and model deployment
I’ve been applying to roles at Amazon, Adobe, Cohere, Optum, and other AI-focused companies, but I’d like to be more strategic.
For those who recently landed AI/ML Engineer, Applied AI Engineer, GenAI Engineer, or MLOps roles:
Which companies are actively hiring AI/ML engineers right now?
Which companies are most open to candidates with 3–5 years of experience?
What job boards, communities, or application strategies helped you get interviews fastest?
Are there any underrated companies I should target?
If you were in my position today, where would you focus your efforts over the next 30 days?
Looking for honest advice, company recommendations, and lessons learned from people who have successfully navigated the current AI/ML job market.
Thanks in advance.

I’m actively looking for AI/ML Engineer opportunities in the U.S. job market and would appreciate some advice from the community.
Background:
• 3+ years of industry experience in AI/ML
• Production ML systems in financial services and healthcare
• Experience with LLMs, RAG, LangChain, LangGraph, Agentic AI, MLOps, AWS, PyTorch, NLP, and model deployment
I’ve been applying to roles at Amazon, Adobe, Cohere, Optum, and other AI-focused companies, but I’d like to be more strategic.
For those who recently landed AI/ML Engineer, Applied AI Engineer, GenAI Engineer, or MLOps roles:
Which companies are actively hiring AI/ML engineers right now?
Which companies are most open to candidates with 3–5 years of experience?
What job boards, communities, or application strategies helped you get interviews fastest?
Are there any underrated companies I should target?
If you were in my position today, where would you focus your efforts over the next 30 days?
Looking for honest advice, company recommendations, and lessons learned from people who have successfully navigated the current AI/ML job market.
Thanks in advance.

I’m actively looking for AI/ML Engineer opportunities in the U.S. job market and would appreciate some advice from the community.
Background:
• 3+ years of industry experience in AI/ML
• Production ML systems in financial services and healthcare
• Experience with LLMs, RAG, LangChain, LangGraph, Agentic AI, MLOps, AWS, PyTorch, NLP, and model deployment
I’ve been applying to roles at Amazon, Adobe, Cohere, Optum, and other AI-focused companies, but I’d like to be more strategic.
For those who recently landed AI/ML Engineer, Applied AI Engineer, GenAI Engineer, or MLOps roles:
Which companies are actively hiring AI/ML engineers right now?
Which companies are most open to candidates with 3–5 years of experience?
What job boards, communities, or application strategies helped you get interviews fastest?
Are there any underrated companies I should target?
If you were in my position today, where would you focus your efforts over the next 30 days?
Looking for honest advice, company recommendations, and lessons learned from people who have successfully navigated the current AI/ML job market.
Thanks in advance.

Hey everyone,
I recently graduated and I’m exploring options between applying on my own vs going through a staffing/consulting agency for jobs in the USA.
I’m mainly looking for:
Genuine agencies with good client connections
Help with resume marketing/interview preparation
Support for OPT/CPT/H1B candidates
Agencies that actually help place candidates instead of just collecting documents
I’m from a tech background and still early in my career, so I wanted honest opinions from people who have already gone through this process.
Which staffing agencies had a good experience for you?
Which ones should be avoided?
Also:
Is it better to apply independently or through staffing agencies in the current market?
Do agencies usually modify resumes for each application or use Easy Apply for bulk applications?
Any red flags I should watch out for before joining?
Would really appreciate real experiences and suggestions. Thanks!

I recently graduated and I’m currently on my initial OPT. I’m confused whether it’s better to apply for jobs on my own or join a staffing/consultancy agency for placements.

For people who already went through OPT:
- Which worked better for you?
- Did staffing agencies actually help with interviews and placements?
- Any red flags I should watch out for?
- Is it harder to get direct company jobs as a fresher on OPT?

Would appreciate honest advice and experiences.