So I’m a final year PhD Student in Germany. I work on Computer Vision. I did quite some good work during my PhD, got around 7 A\* papers in NeurIPS, ICLR, CVPR (2 orals), and ICCV. As my PhD is ending in 3 months I started to search for jobs. I targeted BigTech (those dudes pay tons of cash). I got 2 interviews in one month in 2 BigTech companies. They told me there would be some code, and man after LLMs my algorithmic brain neurons aren’t firing as much. Anyways I practiced, but failed both interviews from the first round cause I couldn’t solve LeetCode. I just don’t understand what does LeetCode have to do with AI jobs? The thing is LeetCode are specific algorithms in CS, not really coding. They measure more your CS algorithmic skills, not your coding skills. You can know how to code very well (like I do) but you can not know how to solve a LeetCode problem because it requires a specific algorithm. I understand that it measures your ability to think outside the box, or it measures your way of thinking, but this is just practice, so at end it’s measuring how good you practiced LeetCode not how good you are at your topic in computer vision ! Even people with 10 years of experience that get laid off from their job gotta start learning LeetCode again from scratch.

It’s just an inherited assessment they took from SDE without adapting it. I work on training large scale diffusion models and still can’t get even an internship because of completely useless things.

Anyways, just wanted to share my frustration. I’m probably going for the academic track, find a PostDoc then to assistant professorship. When I apply for a PostDoc I will be evaluated on my deep learning skills and my publication output , not on some stupid stuff.

Cheers guys

Write and solve numerical math problems, implement solutions in Python or similar tools, and check the results on edge cases. Around 15 flexible hours a week.

You’ll need a completed MSc or PhD in a relevant field, or a completed bachelor’s degree plus 1–2 years of maths-focused work or research at a leading employer or institution.

Interested? Email [email protected] with “Numerical Math MLJ” in the subject. Include your completed degree and a sentence about a numerical problem you worked on.

I’m currently working as an AI/ML associate with zero project experience (placed on bench since joining). Now I badly want to improve my skills and start learning for next 3-4 months. Basically I don’t prefer studying ML in deep and mostly into GenAI. So please suggest me good roadmaps and projects to gain experience. I would like to switch using this project experience. TIA

Hi everyone,

I'm currently pursuing a PhD in ML at a UK university and starting to explore industry research opportunities, primarily in the UK and Europe.

My background:

• Research in self-supervised learning, contrastive learning, JEPAs, and uncertainty-aware representation learning.

• Multiple first-author publications at major computer vision conferences (WACV, ACCV), plus additional publications at other conferences and workshops.

• Around 2 years of experience as a research assistant working on applied computer vision and robotics projects.

• Experience with PyTorch, Python, HPC, and training deep learning models.

• Teaching, research supervision, and peer-reviewing experience.

I'm mainly interested in Research Scientist, Applied Scientist, and research-oriented Research Engineer positions, preferably where I can continue developing novel ML methods rather than focusing exclusively on product development.

I'd appreciate some advice:I'd appreciate some advice!

Thanks!

Is it possible to get a job in AI/ML without having a background in backend and working a backend job?

I really like AI/ML BUT I didn’t work in backend or fullstack just internships, can I get an internship or a job opportunity, or do I need masters?

Thank you all

Write and test Python exercises on model training, inference and debugging. Around 15 flexible hours a week. You’ll need a completed relevant bachelor’s degree and hands-on machine learning work or research experience.

Interested? Email [email protected] with “Junior ML” in the subject and a sentence about what you did on an ML project.

Hey everyone!

I'm looking into the Applied Machine Learning Engineer role at Fireworks AI and wanted to see if anyone here has gone through their interview process recently.

I'd really appreciate any insights on:

• What does the overall interview process look like, and how many rounds are there?

• What should I expect in the technical rounds? Is the focus more on DSA, ML fundamentals, LLM inference/optimization, or ML system design?

• Are there any live coding, PyTorch implementation, or practical ML exercises?

• How deep do they go into topics like transformers, KV caching, model serving, and distributed inference?

• What's the overall difficulty level, and how would you recommend preparing?

Would love to hear from anyone who's interviewed for this role or similar ML engineering positions at Fireworks AI.

Thanks in advance!

Anyone got an invitation for an online assessment (Glider) for Intuit Summer 2027: AI Science Intern? Which topic should I cover to prepare?

I'm a 2027 graduate looking for entry-level opportunities in ML, AI and GenAI. Recently, I've been getting positive responses from startups, which is encouraging. However, I'm increasingly frustrated with their assessment processes.

Some startups ask candidates to build complete applications involving RAG pipelines, AI agents, API integrations, deployment and documentation just to evaluate their skills.

And sometimes it doesn't stop there. The expectation is something like:

"Complete this project first. If we like your work, we'll give you two more projects."

I'm genuinely wondering where we draw the line between a technical assessment and unpaid development work.

I understand that companies need to evaluate candidates. I'm perfectly fine with coding rounds, technical interviews, debugging tasks, implementing specific features or even building a small prototype.

But spending an entire day building a complete application is a different commitment.

There are also actual costs involved. Working with LLMs means consuming API tokens, and those aren't free. I've had to manage my own credits, so repeatedly spending them on recruitment assignments isn't sustainable.

What makes it worse is that some companies don't even provide feedback after submission. You invest hours of work and sometimes receive no response at all.

I believe there are better ways to evaluate ML engineers:

• Discuss existing projects and their technical implementation.

• Ask candidates to explain model choices and architectural decisions.

• Give small, well-defined ML or coding problems.

• Review GitHub repositories and actual engineering work.

• Conduct meaningful technical interviews.

I'm not expecting a job simply because I completed an assignment. I just think candidates deserve some respect for their time and effort.

I currently have three more startup assessments pending, and I'm honestly reconsidering how much time I should invest.

Are you experiencing similar assessment processes ?

I'd genuinely appreciate hearing both candidates' and hiring managers' perspectives.

Seeking software and machine learning engineers for remote contract work designing, debugging, and evaluating coding tasks that test and train frontier AI models.

WHAT YOU'LL DO:
• Stress-test AI-generated Python, C++, and algorithmic code against tricky boundary conditions and edge cases where models fail
• Audit implementations for algorithmic efficiency (Big-O), numerical stability, memory usage, and clean architecture
• Write working reference code and detailed technical critiques explaining the defects

DETAILS:
• Type of work: Freelance/contract for Data Annotation Tech
• Pay: Up to $150+ USD/hr paid via PayPal
• How it works: Pick projects from your dashboard suited to your skills/interests, submit the time it took after completing each task, and withdraw funds a week later (100% self-paced)
• Qualification: One-time online coding assessment required before onboarding

WHO THIS FITS:
• Production software/ML engineering experience, or an advanced CS / ML graduate background
• Fluent in Python, C++, TypeScript, Go, Rust, Java, or C#
• Comfortable analyzing data structures, time/space complexity, and explaining code tradeoffs clearly in English

HOW TO APPLY:
Onboarding requires passing a one-time coding assessment. Because you only get a single attempt and experienced engineers often get tripped up by how the written explanations are graded, I'm happy to share a quick breakdown of what the graders look for along with the direct application for the programming track.

If you're interested (and don't already have an account on the platform), send me a DM with:

1. Your country of residence

2. Your SWE/MLE experience & degree

3. Your primary programming languages and tech stack

4. Your comfort level with data structures, algorithms, and Big-O analysis

5. ~Hours per week available

Thanks for considering. If you're curious about other roles, let me know and I can match what's available to the information you provide.

Hey so basically I am a non degree self taught student who has a diploma '27 in cse..

Do companies asks DSA for AI/ML Roles (specially AI Engg roles) (5 to 8 LPA)

I have learnt ML DL NLP LLM RAG ...

some frontend backend (fastapi CRUD only)

built projects ...

Built an LLM (decoder only transformer) (15M paramater) from scratch in pytorch and trained quantized and evaluated it and then deployed with fastapi + docker integrated frontend too

RAG chatbot (domain specific data)

finetuned LLM with QLoRA

I have solved 50 easy array n string questions on lc ....

Hello everyone, I am currently working remotely as an internship for a startup company as techlead for 1yr now and want to switch to a better pay job

My parents are old and need attention alltime so i have to look for remote jobs. I am looking for ai/ml engineer and frntd/backened developer.

Could somebody help me with it?

Keywords list taken from Resume Fitting

The most commonly scanned keywords in ML engineering and AI job postings.

ML Frameworks

PyTorch TensorFlow Keras scikit-learn XGBoost LightGBM HuggingFace JAX

MLOps & Infrastructure

MLflow Kubeflow Apache Airflow DVC feature store model registry model serving BentoML

Cloud & Compute

AWS SageMaker Google Vertex AI Azure ML CUDA GPU training distributed training Apache SparkRay

Model Development

LLMs large language models transformers RLHF RAG fine-tuning model evaluation A/B testing

Data Engineering

feature engineering data pipelines ETL Apache Kafka data versioning training data label management data preprocessing

Languages & Tools

Python SQL Docker Kubernetes Git Jupyter CI/CD REST APIs

Keywords list taken from Resume keywords

i am a 3rd yr btech student from nit b actively looking for a remote ml intern that gives real exposure and adds upto my resume

Terac is looking for the following:

Subject Matter Experts: Machine Learning Model Evaluation
Location: Remote
Job Type: Independent contractor, ~5 hours of asynchronous work
Pay: $75/hr

Terac is running a paid study on how good machine learning model outputs actually are. The results show where current AI models do well on complex research tasks and domain-specific prompts, and where they still need work.

You review a series of model outputs generated in response to research prompts and rate them for accuracy, relevance and overall quality using a structured rating system. You also write short justifications for your ratings so they can follow your reasoning. It’s about five hours of independent work, and you can do it whenever you want.

They’re looking for subject matter experts from different academic and professional fields with a good eye for detail, like researchers, data analysts, technical writers and domain specialists. You should have expertise in a specialized domain, strong critical thinking, and be comfortable reading complex technical or research text.

Application is done on the platform in three steps: connect your profiles, ID verification (required) and an interview. Payments go out weekly. H-1B and STEM OPT candidates can’t be supported.

Here is the link to the position: Subject Matter Experts: Machine Learning Model Evaluation

2027 Summer Intern, Machine Learning, MS/PhD, Simulation Realism (World Model)
Waymo
Mountain View, CA
$70 an hour

https://www.moaijobs.com/job/2027-summer-intern-machine-learning-ms-phd-simulation-realism-world-model-waymo-9060

Automated Driving Advanced Development Intern, Machine Learning Research
Toyota Research Institute
Los Altos, CA
$45 an hour

https://www.moaijobs.com/job/automated-driving-advanced-development-intern-machine-learning-research-toyota-research-institute-972

2027 Summer Intern, PhD, Machine Learning - Generative World Models & Controllable Waymo
Mountain View, CA
$85 an hour

https://www.moaijobs.com/job/2027-summer-intern-phd-machine-learning-generative-world-models-controllable-simulation-waymo-347

Machine Learning Engineer, Search Quality
Glean
Mountain View, CA, San Francisco, CA
$140,000 - $265,000

https://www.moaijobs.com/job/machine-learning-engineer-search-quality-glean-7227

Software Engineer, Applied Machine Learning
fal
San Francisco, CA
$180,000 - $230,000

https://www.moaijobs.com/job/software-engineer-applied-machine-learning-fal-1820

Machine Learning Engineer, Data Curation - Autonomous Vehicles
NVIDIA
Santa Clara, CA
-

https://www.moaijobs.com/job/machine-learning-engineer-data-curation-autonomous-vehicles-nvidia-8071

Senior Staff Machine Learning Engineer, Perception, Simulation Realism
Waymo
Mountain View, CA, San Francisco, CA
$298,000 - $368,000

https://www.moaijobs.com/job/senior-staff-machine-learning-engineer-perception-simulation-realism-waymo-5562

Staff Machine Learning Engineer
PathAI
Boston, MA
$197,000 - $284,000

https://www.moaijobs.com/job/staff-machine-learning-engineer-pathai-7367

Staff Machine Learning Engineer - Edge AI
Samsara
Canada, Remote
CA170,400-CA234,300

https://www.moaijobs.com/job/staff-machine-learning-engineer-edge-ai-samsara-3568

Senior Machine Learning Engineer
Faculty
Sydney, Australia, Remote
-

https://www.moaijobs.com/job/senior-machine-learning-engineer-faculty-604

Senior Machine Learning Engineer, AI Safety Evaluations
NVIDIA
Santa Clara, CA
$184,000 - $287,500

https://www.moaijobs.com/job/senior-machine-learning-engineer-ai-safety-evaluations-nvidia-17

Staff Software Engineer, ML
Apptronik
Sunnyvale, CA
$285,000 - $340,000

https://www.moaijobs.com/job/staff-software-engineer-ml-apptronik-2568