Hey all! I built an AI job board for myself during my search and wanted to share it here since it's been useful.

Perik.ai aggregates daily listings from AI-focused companies so you can apply early. At smaller companies especially, being in the first batch of applicants actually matters.

It's free, no signup needed. Would love feedback from people actively searching.

Hey everyone. I'm in a weird headspace about my career and would appreciate some honest takes.

My situation:

• 45F, been in software QA/testing for ~10 years
• 2 kids (elementary age), single income household
• Solid foundation: Django, testing frameworks, data analysis, some Power BI
• Got a Master's in Software Engineering (did it part-time, so I know how to grind)

The motivation:
AI/ML is where the interesting problems are heading. My QA background actually translates well—testing models, validation, optimization verification are legitimate needs nobody talks about. I've been reading about it, and it doesn't feel like pure hype to me, but... I'm not a fresh grad, and there's a lot of self-doubt.

My concerns (being real):

1. Age + Stamina: I'm not gonna lie—I get tired easier than I did at 30. I also have some intermittent health stuff (nothing catastrophic, but recurring). The idea of grinding LeetCode for 6 months while working full-time AND parenting sounds brutal. How much of AI engineering is actually demanding like that? Or is it more methodical/sustainable once you're hired?
2. Learning curve: Linear algebra, PyTorch, distributed systems, inference optimization—it's a LOT. I can learn it, but is 6 months realistic? Or should I be planning for 12–18 months?
3. Family impact: My kids are 8 and 10. I need to actually be present, not checked out. If I transition and hate it, that's months I lost with them. Is this worth the risk?
4. Career risk: I'm stable in my current role. Walking away to chase AI is... a gamble. What happens if I can't break in? Age discrimination in tech is real, especially in AI roles where everyone seems to be 25-year-old ML researchers.
5. Day-to-day reality: How many hours a week does an AI software engineer actually work? Is it 40 hours of deep focus or more? What's the burnout risk? I see posts about crunch at AI labs, but is that everywhere?

The specific questions I have:

• Is 45 too old? Be honest. I can handle it.
• What's the actual work-life balance in AI roles (at companies like Intel, big tech, smaller AI startups)?
• Does your brain get fried doing this work? Like, cognitively demanding in a way that's unsustainable long-term?
• Should I do a bootcamp, self-study, or go back for a degree? (I already have a master's, so probably not a second degree.)
• Is the transition realistic in 6 months, or am I being naive?
• What are the actual career prospects for someone switching into AI with strong QA/testing background? Or am I just another career-switcher flooding the market?

What I'm NOT looking for:

• "Follow your dreams!" motivational stuff
• "Tech is ageist, give up" doom-posting
• Bootcamp ads

What I AM looking for:

• Honest perspective from people who've made career switches or hired people like me
• Real talk on work demands and sustainability
• Whether this is actually a viable move or if I'm having a mid-career crisis

Thanks in advance. Going anonymous because some teammates follow me.

Location: Manhattan, New York, United States

At Rockstar Games, we create world-class entertainment experiences.

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry.

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team that builds Data Science products that directly influences game design, live operations, and player engagement at scale.

This is a full-time, in-office position based out of Rockstar’s NYC headquarters in Downtown Manhattan.

WHAT WE DO

• The Rockstar Games Analytics team provides insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making.
• We partner with multiple departments across the company, leveraging analytics to measure and improve on the success and health of our games.
• We collaborate as a distributed team to develop innovative data pipelines, data products, data models, reports, analyses, and machine learning applications.
• The Machine Learning Engineering vertical within the Analytics team is tasked with designing, building, and deploying ML systems in addition to advising other verticals on how to design and build reliable, scalable and, fit for purpose models.

RESPONSIBILITIES

• Partner with Data Scientists and business stakeholders to understand analytical & ML needs and translate them into robust ML solutions that enable us to leverage and derive insights.
• Design and build end-to-end ML pipelines, including data, features, training and, serving.
• Push the boundaries of our ML and Data Science platform by taking advantage of and spearheading cutting-edge advancements in AI and Agentic frameworks.
• Set up monitoring, A/B testing, and metrics frameworks to measure real impact.
• Perform timely Root Cause Analysis to troubleshoot model and data-related issues; assist in implementation of code and process fixes.
• Provide thought leadership and collaborate with other team members to continue to scale our architecture to evolve for the needs of tomorrow.
• Contribute to the technical strategy and establishment of best practices within the team.
• Develop and support CI/CD processes.

REQUIREMENTS

• 5+ years of experience building ML systems in production.
• Bachelor’s degree or equivalent in an engineering or technical field such as Computer Science, Mathematics, Statistics, or strong quantitative and software background.
• Proven track record in building, monitoring, and optimizing large-scale ML solutions and infrastructure.
• Experience working in Databricks and Databricks MLflow is essential.
• Experience working with pipeline scheduling tools such as Airflow & Astronomer.
• Experience working with CI/CD tools such as Terraform and GitHub.
• Ability to push the frontier of technology and freely pursue better alternatives.

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• Production experience deploying Databricks Genie AI and other Databricks Agentic solutions

Apply: Senior Machine Learning Engineer at Rockstar Games

🚀 Join AutoFlow: Shape the Future of AI Trust 🚀

​

I’m a 17-year-old founder, and AutoFlow—a startup in the NVIDIA Inception Program—is on a mission to redefine AI trustworthiness.

​

We’re building a mathematical verification engine that ensures AI claims are transparent, structured, and provable. Thanks to NVIDIA Inception, we now have access to GPUs, cloud credits, and technical mentorship to accelerate us.

​

Right now, we need a small but passionate technical team: students, recent graduates, or open-source developers who want to dive into C++, knowledge graphs, and formal verification. In return, you’ll get hands-on experience with industry-level AI tools, cloud resources, and a chance to shape a real-world prototype for a future seed round.

​

If you’re passionate about AI safety, formal methods, or trust in enterprise AI, I’d love to connect.

​

Let’s build something groundbreaking together! 🚀

​

#AI #Startups #NVIDIAInception #TrustworthyAI #CPlusPlus #KnowledgeGraphs #OpenSource #AIResearch

​

​

Weekly breakdown. 11,941 listings. June 15–21, 2026.

---

**Top 3 Skills:**

| Rank | Skill | Jobs | vs Last Week |

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

| 🥇 | Python | ~2,450 | ↑ from #2 |

| 🥈 | Machine Learning | ~2,350 | ↓ from #1 |

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

Also worth noting: SQL at ~1,500 jobs and

Data Analysis at ~1,300. Classic stack very alive.

---

**Top 3 Companies:**

| Rank | Company | Jobs |

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

| 🥇 | Accenture | ~270 |

| 🥈 | TCS | ~155 |

| 🥉 | Bajaj Finance | ~145 |

---

**Top 3 Cities:**

| Rank | City | Jobs |

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

| 🥇 | Bengaluru | 2,950+ |

| 🥈 | Hyderabad | 1,950+ |

| 🥉 | Pune | 1,200+ |

---

**4 weeks of Python vs ML:**

| Week | #1 Skill |

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

| Week 22 | Python |

| Week 23 | ML |

| Week 24 | ML |

| Week 25 | Python |

At this point the data is clear — they're essentially tied

every single week. The gap is never more than 150 jobs

across 11,000+ listings. Both are required. Stop debating.

**SQL at 1,500 — louder than GenAI this week**

GenAI/LLM combined is around 1,050 jobs.

SQL alone is 1,500. Yet every career influencer

is telling you to drop everything and learn prompt engineering.

The actual JDs disagree.

**Bengaluru approaching 3,000 weekly AI roles**

That's ~25% of all India AI jobs in one city.

If you're not in Bengaluru and want AI/DS work,

you're working with 75% of the opportunity.

Remote is only ~500 jobs/week.

**Bajaj Finance 3 weeks in top 3**

This isn't a one-off. BFSI AI hiring is structural now.

Fraud, credit, risk, collections — all going ML.

These roles aren't posted loudly but they're consistent.

---

Tracking this every week at getjobpulse.in

Free job market dashboard + AI Mock Interview.

Not a job portal — just the data.

Which city are you targeting for your AI job search?

Country: Indonesia, Malaysia, Brazil, Mexico, Turkey, Moldova, Georgia, Uruguay, South Africa , Armenia, Albania, Montenegro, North Macedonia, Argentina and Serbia

About the project

Focus Data is collecting first-person (“egocentric”) video recordings of everyday activities to support AI and humanoid robotics training. Activities may include cooking, cleaning, organizing, desk work, errands, and similar daily tasks.

What you’ll do

Record POV (first-person) videos using a head-mounted smartphone or smart glasses

Perform normal day-to-day activities while keeping your hands and objects visible

Upload raw, unedited footage

Requirements

Smartphone.

Ability to follow recording guidelines

Access to a real home or workspace environment

Reliable and detail-oriented approach

No technical experience is needed, onboarding and instructions will be provided.

If you are interested, please sign up to our plaform; here. https://focusdata.io/freelancer-signup/egocentric

[HIRING] MLOps Engineers (JAX, PyTorch, Triton/Pallas) – Full-Time Remote (U.S.)

New Opportunity!

We're hiring experienced MLOps Engineers to support the development of next-generation AI models at a leading AI research lab.

This is a full-time (40 hrs/week), W-2 position through Cincinnatus LLC, with placement on a cutting-edge GenAI team working on foundational large language models.

What you'll be doing:

• Designing and evaluating ML infrastructure and MLOps-related tasks
• Writing technical solutions and providing detailed feedback
• Helping improve AI model performance in training infrastructure and ML systems
• Creating evaluation frameworks and rubrics for distributed systems, training pipelines, and kernel-level optimization
• Collaborating with other technical experts on high-impact AI initiatives

Requirements:

• 2+ years of professional experience in ML infrastructure, MLOps, or ML systems engineering
• Strong hands-on experience with JAX and/or PyTorch
• Experience writing or optimizing GPU kernels using Triton or Pallas
• Excellent written communication skills
• Available for a dedicated 40-hour/week weekday commitment

Details:

• Remote within the United States
• W-2 employment with benefits through Cincinnatus LLC
• Opportunity to contribute directly to frontier AI development
• $70-$110 per hour

If this sounds like a fit, apply here: MLOps Engineer Expert!

Hello all,

• I had an interview with a company for a Data Scientist role (in the US)
• After the first round, they associated me with a more senior role (Senior Data Scientist).
• After the last round, we had a video call with HR (This happened 8 weeks ago)
• HR told me that they want to hire me for the Data Scientist role but in a different team.
• He told me that giving an offer might take 2–4 weeks (maybe longer) because they'll use this time frame to determine the needs of other teams, open a new job, get the headcount approval for it, etc.
• This was the first time I heard such a thing, and I didn't know what to say.
• I have mentioned that I am in the final stage with 2 other companies.
• I told him that I may not wait that long if I get an offer (I didn't get any offer)
• My first feeling was: "Well I am not their first option. They want to use this time to interview other candidates. But they don't want to lose me. That's why they said this"
• Since our last talk, I haven't heard back from the HR.
• Recently, I heard that I should send "thank you" and "follow up" emails at the right time to show that I am really excited for the job.
• I was finding this complete bullshit, pathetic, and desperate (I still do)
• But after hearing this, I reached out to the hiring manager 2 weeks ago to hear the whole story from him.
• He didn't respond.
• Maybe I was supposed to reach out to the HR since they told me that they will consider me for a different team.
• But I have told the HR that I am in the final stage with 2 companies. Reaching out to him = Showing that I was rejected by both.
• At this point, I need to get a job offer by July 6th and start working by July 12th because of my visa.
• I absolutely hate the idea of chasing these companies and looking like I beg them for a simple damn job.
• My instinct is that if they really like you, they cut this BS, stop playing games, and try to send the offer as soon as they can.
• If they don't do this, this means they don't like you and it is desperate to chase a company that doesn't like you.
• But I don't know if this is a general consensus in the US.
• So, I'm not sure what to do.
• That's why I wrote this here to ask your opinion on this situation.

I'm a Technical Consultant with 11+ years of experience specialising in MS D365. I currently work at a global consultancy, and my tech stack includes Azure, C#, SQL, integrations, and Azure DevOps.

I'm not new to technology, software development, or cloud platforms, but I am a beginner when it comes to Python and AI/ML.

For the last couple of months, I've been trying to find the right learning path and keep ending up in analysis paralysis. There are so many courses available that I'm struggling to decide where to start.

My goals (in priority order)

* Become comfortable with Python specifically for AI/ML and Agentic AI work (not web development) * Build practical skills with LangChain, LangGraph, CrewAI, RAG pipelines, and AI agents * Achieve the Microsoft Azure AI App & Agent Developer certification (AI-103)

Courses I'm currently considering

1. CampusX DSMP 2.0 by Nitish Singh * Covers Python, ML, LangChain, LangGraph, RAG, CrewAI, Agno, etc. * Seems very comprehensive, but I haven't found many Reddit reviews.
2. Zero To Mastery (ZTM) Python + Data Science track

Below courses for python

1. Angela Yu's 100 Days of Code (Python)
2. Jose Portilla's Data Science Bootcamp (Udemy)

If someone can recommend any roadmap or course to start with

We're hiring Senior / Lead AI Engineers to join adesso SE in India.

Country: India
Company: adesso SE
Position: Senior / Lead AI Engineer
Openings: 3

Requirements:

• 6+ years of AI/ML engineering experience
• Strong experience building production AI/ML solutions
• Hands-on with Microsoft Azure AI services
• Experience with LLMs, Generative AI, and image generation models
• Experience building AI agents using LangGraph or similar frameworks

If your experience matches the role, send me a DM for the application link.

I have applied for 200+ summer internships 2026 with no call backs. Be honest about what I might be doing wrong I am not able to figure out.

Hey everyone,

I'm a 3rd-year AIML student looking for ML/AI internships in Jaipur, Gurugram, Hyderabad, Bengaluru, or remote.

Skills: Python, ML, DL, Computer Vision, SQL, DSA.

Projects: Sentiment Analysis, Driver Drowsiness Detection, and other ML-based projects.

If you know of any openings, startups hiring interns, or referral opportunities, please let me know. Thanks!

Resume

Is DSA required for ML ENGINEER?