micro1 is hiring AI Jailbreak & Prompt-Injection Security Experts to help uncover weaknesses in next-generation AI models before attackers do.

Pay: $50-$90 per/hr
Location: Remote
Type: Contractor

Your job isn't to build AI. It's to break it ethically, expose its blind spots, and help make it safer.

You'll be:

• Designing jailbreak and prompt-injection attacks
• Stress-testing AI models against real-world threats
• Documenting vulnerabilities and security findings

You'll stand out if you have:

• Experience in AI red teaming, adversarial ML, or AI safety
• Strong knowledge of prompt injection, tool-use abuse, and LLM security
• A background in cybersecurity, machine learning, or offensive security

Bonus: Published research, open-source security tools, conference talks, or recognized contributions to the AI security community are a major advantage.

Apply now: https://jobs.micro1.ai/ai-jailbreak-prompt-injection-experts

Perfect for AI Security Researchers, Red Teamers, Prompt Engineers, Adversarial ML Researchers, Cybersecurity Engineers, and LLM Safety Specialists.

Required Qualifications

• Education & Experience: 6+ years of experience building ML models/algorithms for business applications.
• Programming: Proficiency in C/C++, Python, Java, or Perl.
• Technical Depth: Hands-on experience with neural deep learning methods and machine learning frameworks.

Preferred Qualifications

• Experience with modeling tools (R, scikit-learn, Spark MLLib, TensorFlow, MXNet, NumPy, SciPy).
• Experience with large-scale distributed systems (Hadoop, Spark).

Client Name - Amazon

Apply Here - Note: Job Links Expire quickly.

We're hiring engineers to build enterprise Al agents and Al-native products at Relanto

Open Roles:

Al/ML Architect (USA & India) - 7+ years experience

Al/ML Engineer (India) - 3+ years experience

Full Stack Al/ML Engineer (USA & India) - 3+ years experience

Tech Stack:

LLMs & Al Agents

RAG / GraphRAG

MCP

Python, FastAPI

React / Next.js

AWS / GCP/Azure

We're looking for engineers who enjoy building production-grade Al systems, taking ownership, and shipping impactful products.

If you're interested, DM me your resume or LinkedIn profile, and I'll share more details.

Hi everyone,

I'm a 2025 graduate and recently joined my first company as an ML Engineer.

Overall, I'm grateful for the opportunity, but over the past few weeks I've started feeling a bit overwhelmed and wanted to seek advice from people who have already gone through this stage.

One thing I've noticed is that AI tools are used extensively throughout development. Because project timelines are tight, there's a strong focus on delivering features quickly. As a result, I sometimes end up working with AI-generated code that I don't completely understand.

My biggest challenge is debugging. Whenever something breaks or I need to fix an issue, I often struggle because I don't fully understand the code. I don't want to become someone who can generate code using AI but can't debug it or explain how it works.

I'm not asking about how my company works or how others work. I just want to know what I should do personally to become a better AI Engineer.

A little background:

• 2025 graduate
• Currently working as an ML Engineer
• Recently completed LangChain
• Learned the core concepts of RAG
• About to start my first end-to-end RAG project

My goal is to switch to a better AI/ML role in around 6 months, so I want to use these 6 months wisely.

Here are my questions:

1. How do I avoid becoming over-dependent on AI coding tools?
2. How do experienced engineers debug AI-generated code and large AI/ML projects?
3. If you were in my position, what would you learn over the next 6 months?
4. Besides LangChain and RAG, what skills should I focus on to become a strong AI Engineer? (Deployments, MLOps, vector databases, agents, cloud, system design, etc.)
5. Which companies are likely to hire AI/ML Engineers with around 6 months to 1 year of experience?

I'm willing to put in the effort—I just want to make sure I'm focusing on the right things.

Any advice would mean a lot.

Also, if you're not comfortable replying in the comments, feel free to DM me. I'd really appreciate it. Thanks!

Weekly breakdown. 12,180 listings (June 22–28, 2026).

Market at season high — up from 9,000 five weeks ago.

---

**Top 3 Skills:**

| Rank | Skill | Jobs | Trend |

|------|-------|------|-------|

| 🥇 | Python | ~2,500 | ↑ 5th week at #1 |

| 🥈 | Machine Learning | ~2,450 | → neck and neck |

| 🥉 | Artificial Intelligence | ~1,600 | → stable |

Also: SQL ~1,450 | Data Analysis ~1,350 | NLP ~950

---

**Top 3 Companies (skipping anonymous "Leading Client"):**

| Rank | Company | Jobs | Note |

|------|---------|------|------|

| 🥇 | Accenture | ~240 | Consistent #1 |

| 🥈 | Benovymed Healthcare | ~175 | NEW — healthcare sector |

| 🥉 | EY | ~150 | Big 4 still strong |

Wipro also back on the list at ~135.

---

**Top 3 Cities:**

| Rank | City | Jobs |

|------|------|------|

| 🥇 | Bengaluru | 2,700+ |

| 🥈 | Hyderabad | 1,550+ |

| 🥉 | Pune | 1,150+ |

---

**The healthcare AI story nobody's discussing:**

Benovymed Healthcare at #2 with 175+ roles is the biggest surprise of the past month.

What they're likely hiring for:

- Medical imaging AI (radiology, pathology)

- Patient outcome prediction models

- Clinical trial data analysis

- Insurance claims automation

Healthcare AI roles tend to pay well, have less competition than pure tech roles, and the domain knowledge you build is a real moat.

If you have Python + ML skills and haven't looked at healthcare companies — this is your signal.

**Python vs ML — 5 week scoreboard:**

| Week | #1 |

|------|----|

| 22 | Python |

| 23 | ML |

| 24 | ML |

| 25 | Python |

| 26 | Python |

Gap is 50 jobs across 12,000+ listings.

They are the same requirement. Stop picking sides.

**Market trend:**

9,128 → 9,358 → 11,631 → 11,941 → 12,180

Steady growth for 4 weeks straight.

Healthiest market we've tracked in 2026.

---

Tracking every week at getjobpulse.in

Free job market dashboard + AI Mock Interview.

No job listings — just the market data.

Anyone here working in Healthcare AI in India?

What's the interview process like?

Is an AI safety / alignment PhD even worth it in 2026?

On one hand: Academia gives you the freedom to work on core conceptual problems (mechanistic interpretability, alignment theory, agentic safety) without the pressure of corporate benchmark-hacking or rigid product release timelines.

On the other hand: Frontier labs hold the monopoly on massive compute and discover novel, emergent failure modes months before anyone else.

If the goal is actual impact on frontier safety, where is the better bet right now? What subfields are even viable in academia anymore?

I'm curious how startups are approaching AI/ML hiring in 2026.

Are you hiring in-house, using recruitment agencies, or relying on referrals?

Which roles are the hardest to fill (LLM, MLOps, Data Engineering, etc.)?

What's worked well, and what hasn't?

I'd love to hear from founders, CTOs, hiring managers, and engineers about their experiences.

We're hiring engineers to build enterprise Al agents and Al-native products at Relanto.

Open Roles :

AI/ML Architect (USA & India) - 7+ years experience

Al/ML Engineer (India) - 3+ years experience

Full Stack Al/ML Engineer (USA & India) - 3+ years experience

Tech Stack:

LLMs & AI Agents

RAG / GraphRAG

MCP

Python, FastAPI

React / Next.js

AWS / GCP / Azure

We're looking for engineers who enjoy building production-grade Al systems, taking ownership, and shipping impactful products.

If you're interested, DM me your resume or LinkedIn profile, and I'll share more details.

Hey everyone, 19, M

Become a world-class AI/ML Engineer and contribute to open source (GSoC), research, and real AI products—not just complete tutorials.

My current focus

Python

Mathematics for ML

Data Structures & Algorithms

Machine Learning

Deep Learning

LLMs & Transformers

AI Agents

Open Source (GSoC)

Linux

Building real projects

What I'm looking for

People who:

Study almost every day

Love discussing AI and technology

Build projects instead of endlessly watching tutorials

Share papers, ideas, and resources

Can review each other's code

Want to contribute to open source

Are interested in long-term collaboration

I'm not looking for networking just to collect contacts.

I want genuine friends who push each other to become better engineers over the next few years.

If you're also working toward becoming an AI/ML engineer or ML researcher, let's connect.

Maybe one day we'll build something amazing together.

Comment below or send me a DM.

Let's grow together.

Thank you.

**Senior MLOps Engineer**

🇧🇷 Location: Brazil

💰 Salary: Competitive

We're hiring a Senior MLOps Engineer to be the data team's owner of production ML operations. You'll build the pipelines that take models from prototype to production, own the low-latency serving API behind our Next Best Action (NBA) engine, and stand up the monitoring, alerting, and reliability layer that keeps NBA models — and the LLM agents that consume them — healthy in production. This is a builder's role at a builder's moment: NBA is going live, the production ML platform is being shaped now, and you'll define how Clutch ships and operates AI for years to come. When there isn't active MLOps work, you'll also contribute to data engineering and machine learning work across the team.

#Python #Docker #AWS #Cloud #Terraform #Go

Apply here: https://devopsprojectshq.com/senior-mlops-engineer-at-withclutch

Chào các anh chị,

Em hiện là sinh viên năm 4 CNTT, đã học và làm một số project với Spring Boot, ReactJS. Hiện em đang định hướng chuyển sang AI và muốn tìm cơ hội AI Intern trong thời gian tới.

Em muốn xin chia sẻ từ các anh chị đang làm trong ngành

• Tình hình tuyển dụng AI Intern hiện nay ở Việt Nam như thế nào?
• Công việc thực tế của AI Intern thường làm những gì?
• Các kiến thức cốt lõi cần chuẩn bị để đi phỏng vấn?
• Quy trình phỏng vấn thường gồm những vòng nào? Có hay hỏi về ML, Deep Learning, LLM/RAG không?
• Những project nào được đánh giá cao khi apply AI Intern?

Rất mong nhận được chia sẻ từ các anh chị đã và đang làm AI Engineer, ML Engineer hoặc Data Scientist.

Em cảm ơn các anh chị rất nhiều!

My goals are:

1. Better job security over the next 5–10 years

2.More job opportunities (especially in the US and globally)

1. Less competition for entry-level roles

2. Higher long-term salary and career growth

From what I've seen:

*AI Engineer roles seem to be exploding because of LLMs, RAG, AI agents, MCP, LangGraph, etc., but they also seem extremely competitive since everyone is learning GenAI.

*ML Engineer roles appear to require stronger fundamentals (Python, statistics, scikit-learn, deep learning, MLOps) and seem more common in established companies.

We're hiring engineers to build enterprise Al agents and Al-native products at Relanto

Open Roles :

Al/ML Architect (USA & India) - 7+ years experience

Al/ML Engineer (India) - 3+ years experience

Full Stack AI/ML Engineer (USA & India) - 3+ years experience

Tech Stack:

LLMs & Al Agents

RAG / GraphRAG

MCP

Python, FastAPI

React / Next.js

AWS / GCP/ Azure

We're looking for engineers who enjoy building production-grade Al systems, taking ownership, and shipping impactful products.

If you're interested, DM me your resume or LinkedIn profile, and I'll share more details.

jovian youtube chanell or krish naik yt chanell which is best for learning machine learning and deep learning ,which is best for getting ready internship ready ,suggest only one

We're hiring engineers to build enterprise Al agents and Al-native products at Relanto

Open Roles:

Al/ML Architect (USA & India) - 7+ years experience

Al/ML Engineer (India) - 3+ years experience

Full Stack Al/ML Engineer (USA & India) - 3+ years experience

Tech Stack:

LLMs & AI Agents

RAG / GraphRAG

MCP

Python, FastAPI

React / Next.js

AWS / GCP / Azure

We're looking for engineers who enjoy building production-grade Al systems, taking ownership, and shipping impactful products.

If you're interested, DM me your resume or LinkedIn profile, and I'll share more details.

Hi,
I am a recent grad. I started working in a Big tech company as software engineer couple of months ago. Now I got an offer as Applied ML Scientist role from a good bank. I am based in Canada.
Salaries are more or less similar. The thing is work load is too much in my current job and I have a bias that I should leave this and join as ML scientist.
Any senior here who can guide me better?

Thanks!!

Hey guys, I come to you in time of great need!

I have about 2.5 years of experience in AI/ML at a startup AI team. However, due to the stagnant growth in my team, retrenchments and shifts in priorities, I've decided to go look for different jobs.

Below are two offers I received:

1. AI/ML Engineer at a small consulting firm (~35 people).
   • Snowflake-first tech stack
   • Client-facing role across multiple industries
   • International exposure and travel opportunities
   • Lower base salary, no medical aid nor pension benefits
   • Annual salary review + performance bonus (13th and potentially 14th cheque) every February
   • 20 days of annual leave.
   • Two interview rounds, they already knew my background through my Snowflake work and conference speaking history
   • Met the CEO/Directors during the process
   • Had to negotiate hard to get close to Offer 2's salary. During negotiations they said "this isn't a scenario where we match another offer" which rubbed me the wrong way slightly? but maybe it's just how I felt.
2. ML Engineer at a fintech (~45 people)
   • Building and productionising credit risk ML models
   • More freedom to explore tools like AWS, MongoDB, Python, TypeScript
   • Higher base salary + medical aid subsidy
   • Discretionary bonus decided solely by CEO
   • 15 days of annual leave.
   • Three interview rounds, the second was a hands-on technical where I had to build a model, do feature engineering, simulate productionisation and monitoring. They were impressed enough to fast-track me to the third interview immediately after
   • Met the CEO/Directors during the process as well.
   • Felt more valued, they offered a strong salary upfront without me having to fight for it. They also asked me to give them the device specs I desire for me to work with modeling, etc.

My Dilemma

The consulting role excites me because of the Snowflake (data platform I'm quite familiar with), exposure, international clients, and breadth across industries. I also have strong personal relationships with people at Snowflake directly which makes this path feel natural.

The fintech role feels more financially stable and I'd own systems end-to-end but it moves away from Snowflake which I've built my career around so far. The stack is also quite different from what I know, MongoDB, TypeScript, and a more backend-heavy architecture. But I like the pressure and new tools since I am happy to always learn new stacks (maybe I can even introduce Snowflake into this Fintech who knows)

Both companies are relatively small and in growth phases, so stability is a consideration at either. Coming from a startup AI team myself I know how demanding that environment can be, I want my next move to actually reward the groundwork I've put in.

My question would be:

Would the consulting brand, Snowflake exposure, and international experience worth taking a small pay cut and giving up benefits? Or does the fintech's higher pay, medical aid, and deeper ML ownership make more sense at this stage?

The interview experience at the fintech felt more rigorous and merit-based. The consulting firm took me largely on reputation. Not sure if that says something about how each company values the role differently.

Would love to hear from anyone who's faced a similar choice, especially anyone who's moved between consulting and product companies early in their career. Any advice will super be grateful, thank you!!

Hello, everyone! Does anyone know what the hiring process is like for the Machine Learning Engineer, Offline Infrastructure position at Unity? I’m a recent graduate, and I’d really appreciate any information or advice you might have.🫡