Thread regarding Chevron Corp. layoffs

i guarantee that the majority of the applicants for those jobs are from india, and they skirt around the question about work authorization and sponsorship in the future.

the ironic thing is that we are offshoring those jobs to the less qualified people in india because the better ones are in the states, applying to these jobs to stay here on US payroll.

i read the job description. EAI is dreaming if they think we can get people who know how to fine tune frontier models. this is not meta. i heard we had hundreds of applicants for each position. is that verifiable. why would anybody choose to work in this dumpster fire if they got those skills.

@15f all of the good ones in IT got pulled out of their teams and doing work elsewhere in the org now. IT completely decimated by LC

@te Sorry, yes I meant in IT specifically.

Totally agree that engineers in the business are actually using ML and optimisation to solve problems where they are free from interference from IT.

I meant what ML/AI solutions has IT deployed. As far as I am concerned, IT is a shipwreck full of POs that mostly have no clue.

@te

exactly. it’s a tool bag and techniques. it’s not a product in of itself

i only see completely clueless people question it as if it’s a solution by itself

@q1 u must be another sore loser in the IT department. here's some truth for you. real engineers in the business are already using these in our day to day. your people are not reviewing our models because you had to go through your IT program managers and stupidass teams like ATS even begin to do any work at all. i just see really pointless "AI-ready" metrics that your org is coming up with and all the rhetoric about how data is not ready to do stuff. more mumbo jumbo that doesn't matter.

i have used AI for scripting and ML for my models and done assurance reviews with the subsurface functions for my day to day. there were not IT orgs involved. I know who the good IT people are to get me access to data and compute. We come up with asset plans, well designs. We execute. We operate. The business performance is actually the best that it's ever been. Was it because of AI or ML? who cares? It's just a thing we use.

@kq so where is ML being used in Chevron to actually deliver business outcomes, and make predictions that genuinely influence strategic decisions?

I’ve seen a whole bunch of models that have been deployed that pass Chevron’s touchy-feels model review process (because everyone’s too nice), that would be laughed out of the room in any other company.

I’ve seen people make deceptive claims about the predictive power of their models, have it pass model review which scarcely any real scrutiny, and approved into production by a product owner that doesn’t know better.

So, again, what ML solutions in Chevron are genuinely moving the needle?

They posted the job since the last DEI Data Science hire, Siri, elected to take a package since she wasn't promoted to Chapter Head.

@kq

normies never learned about machine learning models, it’s all chat bots to them always has been

predicting a price a competitor will use tomorrow or how equipment will fail to do predictive maintenance are invisible to them and therefore don’t exist. it’s also impossible them for an algorithm to be an output. it all has to be physical singular component products or its inconceivable. i learned this long ago

@e4 AI and ML is not just chatbots. Just because you don’t see it doesn’t mean it’s not being used under the covers or behind the scenes.

@e4 yes, there are quite a few.

once you actually either get your head out of the sand, or maybe come up out of the water for a breath from having written your ADO stories so that LC can have his perfect power BI dashboard reports on devops velocity, and look at what the scientists and engineers are doing day to day.

stop thinking about an AI solution or application here or there. people are using how it's supposed to be used. scripting, coding, automating things... all without the IT project managers telling them what the process is for work intake in this whole new op model.

Can anyone name an AI/ML solution that’s been rolled out within Chevron in the past twelve months that is actually in the hands of customers and actually works?

I know there’s a lot of product owners claiming their tools are in the wild, delivery results and generating value — but any first-hand sightings?

@OP it's not just that job. they have 3 other roles out there. all in the US. all while the DNI positions that were slated to go external in the US were all pulled last minute by LC and replaced by ENGINE roles.

linkedin says that their data engineering position is trending and hot.
i guess it does have lots of applicants. it's unfortunate that IT decided to offshore all those jobs when people here still surprisingly want to work at chevron.

It speaks volumes that EAI gets to hire US talent and DNI only gets ENGINE as replacements for any attrition.

It tells you the direction of where IT is headed. We already knew this, but this is really something else…

I referred a few folks just to get my referral bonus since my actual bonus will su-k so bad

The funny thing is that enterprise AI posted these roles because LC and AK’s strategy is to offshore everything and IT has lost all the talent.

These roles are all non-IT positions and supposedly has hundreds of applicants…

@bn

that’s different a huge tell

if they could outsource this, they would

@ay yep we had a few good people in SR for that role and they let them walk. Oh well, that’s what you get with leaders who only have short term vision

Will the successful candidate have to use Research Canvas, Azure ML and Windows?

@ay just here to appreciate the use of one of my favourite verbs, to "enshittify". Have not heard it used in relation to Chevron, but it fits so beautifully, absolute poetry 😂

I am surprised Chevron isn't dredging that alleged "high-caliber talent pool" in Bangalore to fill this job. Regardless of the country, I'm assuming that anyone with the required background would prefer blue-chip tech companies or high-potential startups to the wheezing dinosaur that is O&G.

It's funny actually, we lost lots of folks that were qualified for that role. I think there is an idea and attitude that the new batch will accept the current enshittified working conditions as the status quo, the ones that left were disgruntled.

it’s interesting how people seem to think these jobs are easy and that just any random laid off person can roll out of bed and do them well

it really speaks volumes to how much distrust IT and data orgs have built and how much na--d incompetence they have displayed over the years.