#machine learning developers

[gwebpro]

Factors to Consider When Hiring Machine Learning Developers

Hiring machine learning (ML) developers involves assessing various factors to ensure their suitability for the role. Candidates must be proficient in both technical and soft skills; otherwise, they may not be a good addition to your team. For instance, miscommunication is possible if they lack effective communication skills, which can hinder teamwork.

To hire a competent machine learning developer with all the skills you require, let’s look at the qualities you need to look for. 

What to Look for When Hiring Machine Learning Developers

Let's look at the characteristics that set top machine learning developers apart. Doing so will make hiring them that much easier. 

Educational Qualifications

When looking for a skilled machine learning developer, take into consideration the applicant’s education. As machine learning is part of computer science, a background in computer programming, mathematics, and data science is mandatory. Candidates with a bachelor's degree with certifications in machine learning are accepted, whereas candidates with a PhD are preferred.

Candidates must also be experts in topics like machine learning algorithms, natural language processing, regression, and neural networks. They must also be fluent in computer programming languages. 

Technical Skills

Applicants for your machine learning developer role must have superior technical skills. They are expected to be acquainted with programming languages like Python, C++, JavaScript, Java, C#, Julia, Shell, R, TypeScript, and Scala. They must also be familiar with data engineering, data analysis, ML models, and deployments. In brief:

Data engineering is managing or transforming data for storage and processing.

Data analysis is the process of examining, purifying, converting, and modelling data in order to extract meaningful information.

Machine learning models are programs that identify patterns or draw conclusions from unknown data sets.

Model deployment is the process of incorporating an ML model into an already-existing production so that it can receive input and produce output.

Software Engineering Skills

Software engineering skills are a must-have for machine learning developers. Writing search queries, sorting, and optimizing algorithms are required, along with being familiar with data structures like stacks, queues, trees, graphs, and multidimensional arrays. 

AI and machine learning developers must also know about computer architecture elements like memory, clusters, bandwidth, deadlocks, and caches. These are some of the fundamentals of computer science.

Soft Skills

The recruiter must ensure that applicants have soft skills as well as technical ones. While machine learning is a technical domain, having soft skills like problem solving and clear communication makes a candidate more efficient in their work. This is because one of the most important aspects of the work is being able to explain the project's objectives, schedule, and expectations to stakeholders.

Also, the goal of machine learning is to solve problems in real-time. This means having the critical and creative thinking skills necessary to identify problems and come up with solutions.

Time Management and Teamwork

Time management skills are essential for making significant contributions to the team. Machine learning developers frequently have to balance the needs of multiple stakeholders while still finding time to conduct research, plan and manage projects, and create and thoroughly test software.

Teamwork is also crucial as machine learning developers often work closely with software engineers, marketers, product designers, managers, testers, and data scientists. They are frequently at the core of AI business initiatives. When recruiting an AI/ML developer, supervisors look for the ability to work well with others and contribute to a positive work environment.

A Desire to Learn New Things

An AI/ ML developer must have a passion for studying and learning. Artificial intelligence, deep learning, machine learning, and data science are quickly developing topics. The most successful AI/ML developers are always updating their knowledge and willing to learn new abilities. Even machine learning developers with doctoral degrees find ways to stay up to date by attending boot camps and workshops and doing self-study. 

Developers must study cutting-edge methodologies and technologies, learn the newest programming languages, and become proficient with new applications and tools. An enthusiastic learner quickly learns about the newest industry developments. 

Cost and Value

Recruiters must know the market value of these positions in order to hire a developer. A typical AI/ML developer's hourly rate in Canada could differ depending on their position, degree of expertise, region, and demand within the market. In Canada, AI/ ML experts are hired with an hourly pay between $30 and $60 on average.

Entry-level jobs such as junior data analysts or AI assistants have a pay between $30 and $40 per hour. Professional-level AI/ML developer costs are typically between $40 and $60. These experts have the knowledge and expertise required to take on challenging AI projects and produce top-notch results. 

When hiring a machine learning developer, a good mix of technical and soft skills is needed. A solid educational base, command of important programming languages, and familiarity with data engineering are all desirable. Teamwork, effective communication, and problem-solving skills are also vital. You are sure to locate the perfect developer for your team by keeping these things in mind.

[solulab76]

Our Machine Learning Development Services offer a comprehensive range of solutions to meet your business needs. From data analysis to algorithm development, we specialize in creating customized Machine Learning solutions that drive business growth.

[whump-in-the-closet]

characters who’s identity revolves around their purpose, defined by something or someone else. By the prophecies, by their service; the lapdog, the weapon, the chosen one. And then there’s a moment of softness, a complete breach and utterly human— they cradle their head in their hands, they bend to pick up a cat and hold it tight, they slump against someone’s shoulder, completely trusting for the first time

thank you that’s it. exits stage and screams.

[nixcraft]

Imagine being this stupid to drink Kool-Aid and giving a remote LLM tool full access to your codebase, and, in many cases, not maintaining backups or using proper Git with permissions. How these guys are getting hired to write code is beyond me.

[puppetmaster13u]

hi I’m back again to ask about the down in the deep au

How’s Danny handling the whole deaged/transformation into sea Creature/melding/not having his full power set? Also how is he feeling about his new guardian figure(?)

Does he miss his human feet

Are you in my google docs lol?

He actually is more than a hint hysterical when he first realizes his legs are gone. And doesn't realize how 'small' he is at first or that he doesn't have his powers thanks to the fact he was already exhausted and such from his Wail and previous battle. Needless to say he does kind of panic when he realized that the few powers he has are limited AF.

He's actually kind of neutral towards Sebastian at first, but does end up warming up towards him. Er, it takes a tiny bit at first because he holds a grudge for carrying him everywhere, he's sure this place can't be more dangerous than other places he's been!

He's actually struggling with not having legs, seeing as the only time he's had a ghost tail, or any tail really, up until this point is in flight. And it didn't have a fin, so he's incredibly clumsy. (There are many swimming lessons in his future to help him get used to legless movement, along with a bit of hand-holding to his embarrassment)

So all in all, he could be handling it worse at the moment. Could be handling it better, but he could be handling it worse too.

[sag-dab-sar]

Clarification: Generative AI does not equal all AI

💭 "Artificial Intelligence"

AI is machine learning, deep learning, natural language processing, and more that I'm not smart enough to know. It can be extremely useful in many different fields and technologies. One of my information & emergency management courses described the usage of AI as being a "human centaur". Part human part machine; meaning AI can assist in all the things we already do and supplement our work by doing what we can't.

💭 Examples of AI Benefits

AI can help advance things in all sorts of fields, here are some examples:

Emergency Healthcare & Disaster Risk X

Disaster Response X

Crisis Resilience Management X

Medical Imaging Technology X

Commercial Flying X

Air Traffic Control X

Railroad Transportation X

Ship Transportation X

Geology X

Water Conservation X

Can AI technology be used maliciously? Yeh. Thats a matter of developing ethics and working to teach people how to see red flags just like people see red flags in already existing technology.

AI isn't evil. Its not the insane sentient shit that wants to kill us in movies. And it is not synonymous with generative AI.

💭 Generative AI

Generative AI does use these technologies, but it uses them unethically. Its scraps data from all art, all writing, all videos, all games, all audio anything it's developers give it access to WITHOUT PERMISSION, which is basically free reign over the internet. Sometimes with certain restrictions, often generative AI engineers—who CAN choose to exclude things—may exclude extremist sites or explicit materials usually using black lists.

AI can create images of real individuals without permission, including revenge porn. Create music using someones voice without their permission and then sell that music. It can spread disinformation faster than it can be fact checked, and create false evidence that our court systems are not ready to handle.

AI bros eat it up without question: "it makes art more accessible" , "it'll make entertainment production cheaper" , "its the future, evolve!!!"

💭 AI is not similar to human thinking

When faced with the argument "a human didn't make it" the come back is "AI learns based on already existing information, which is exactly what humans do when producing art! We ALSO learn from others and see thousands of other artworks"

Lets make something clear: generative AI isn't making anything original. It is true that human beings process all the information we come across. We observe that information, learn from it, process it then ADD our own understanding of the world, our unique lived experiences. Through that information collection, understanding, and our own personalities we then create new original things.

💭 Generative AI doesn't create things: it mimics things

Take an analogy:

Consider an infant unable to talk but old enough to engage with their caregivers, some point in between 6-8 months old.

Mom: a bird flaps its wings to fly!!! *makes a flapping motion with arm and hands*

Infant: *giggles and makes a flapping motion with arms and hands*

The infant does not understand what a bird is, what wings are, or the concept of flight. But she still fully mimicked the flapping of the hands and arms because her mother did it first to show her. She doesn't cognitively understand what on earth any of it means, but she was still able to do it.

In the same way, generative AI is the infant that copies what humans have done— mimicry. Without understanding anything about the works it has stolen.

Its not original, it doesn't have a world view, it doesn't understand emotions that go into the different work it is stealing, it's creations have no meaning, it doesn't have any motivation to create things it only does so because it was told to.

Why read a book someone isn't even bothered to write?

Related videos I find worth a watch

ChatGPT's Huge Problem by Kyle Hill (we don't understand how AI works)

Criticism of Shadiversity's "AI Love Letter" by DeviantRahll

AI Is Ruining the Internet by Drew Gooden

AI vs The Law by Legal Eagle (AI & US Copyright)

AI Voices by Tyler Chou (Short, flash warning)

Dead Internet Theory by Kyle Hill

-Dyslexia, not audio proof read-

[rthidden]

What is an Algorithm in 30 Seconds?

An algorithm is simply a series of instructions.

Think of a recipe: boil water, add pasta, wait, drain, eat. These are steps to follow.

In computer terms, an algorithm is a set of instructions for a computer to execute.

In machine learning, these instructions enable computers to learn from data, making machine learning algorithms unique and powerful.

[jaguarsoup]

I’m bringing back the oc guys

I don’t think I ever posted the old images of them on here but. Alas

This is basically what happened when I watched httyd and saw hiccup make that like wingsuit thing, and I was like “what if that, but more”. So this guy basically abandoned society to become dragon very cool very based yada yada.

I’ve done like a bunch of obsessive thinking over how literally any part of this armor/wingsuit thingy would actually work, and um. don’t worry about it alright. The tail proportions are off but I’m not gonna fix that right now

||DO NOT FEED TO AI DO NOT USE FOR MACHINE LEARNING||

[whispersoftheunheard]

Coding: My Escape, My Obsession

Programming—ahh, what a paradox! Sometimes it’s an absolute thrill, and other times, it’s the most stressful thing ever. For me, coding isn’t just a skill; it’s my escape. Whenever life gets heavy, my mind instinctively drifts to programming. New ideas, fresh logic, endless possibilities—it’s like therapy but with syntax errors.

But somewhere along the way, this escape became a full-blown obsession. My four years of engineering? A blur of code, projects, and fixing bugs—mine and everyone else's. I was always working, always solving something. And now, when I look back, I struggle to find those carefree moments of pure fun. Sure, I enjoyed college, but every memory somehow loops back to programming.

I don’t regret it. I don’t claim to be a coding genius either—I’m still learning, still growing. But one thing’s for sure: programming has shaped me in ways I never imagined. It gave me purpose, resilience, and a language beyond words.

Yet, here’s what I’ve realized—life isn’t just about writing perfect code; it’s about writing a story worth remembering. And while programming will always be a part of me, I want to step beyond the screen, embrace new experiences, and create moments that don’t just end in a semicolon.

Because in the end, the best code I’ll ever write is the one that balances passion with life itself.

[shygals-slophouse]

I would like to request roxy lalonde from homestuck who's boobs are slowly growing bigger and bigger, if you wanna make it a sequence that's up to you!

I fell off of Homestuck before I really got to know Roxy, Dirk and the like, but assuming she follows the typical Homestucker journey: here's a few stages of her adventure.

[afantasyoffiction]

maybe it’s all gonna be ok maybe ai will lead to more human-created art not less maybe humanity’s spirit will survive itself once again

[theoraeeken]

something about how the mcmg went from looking like the kind of guys you'd match with on tinder in a fit of self destruction horniness, to just like... men who listen to dad rock. chris sabin looks like he works in a marketing firm. alex shelley looks like he teaches drum lessons. compelling. really truly compelling. and weirdly hot.

[nixcraft]

[softwaredevelopmenthub25]

Explore the innovative software development services offered by Software Development Hub (SDH). From MVP development and AI-powered solutions to ERP software, IoT, and cloud migration, SDH delivers cutting-edge expertise for startups and businesses worldwide. Discover insights, project highlights, and tips on building user-centric applications and driving digital transformation.

[jcmarchi]

Researchers detect a new molecule in space

New Post has been published on https://thedigitalinsider.com/researchers-detect-a-new-molecule-in-space/

Researchers detect a new molecule in space

New research from the group of MIT Professor Brett McGuire has revealed the presence of a previously unknown molecule in space. The team’s open-access paper, “Rotational Spectrum and First Interstellar Detection of 2-Methoxyethanol Using ALMA Observations of NGC 6334I,” appears in April 12 issue of The Astrophysical Journal Letters.

Zachary T.P. Fried, a graduate student in the McGuire group and the lead author of the publication, worked to assemble a puzzle comprised of pieces collected from across the globe, extending beyond MIT to France, Florida, Virginia, and Copenhagen, to achieve this exciting discovery. 

“Our group tries to understand what molecules are present in regions of space where stars and solar systems will eventually take shape,” explains Fried. “This allows us to piece together how chemistry evolves alongside the process of star and planet formation. We do this by looking at the rotational spectra of molecules, the unique patterns of light they give off as they tumble end-over-end in space. These patterns are fingerprints (barcodes) for molecules. To detect new molecules in space, we first must have an idea of what molecule we want to look for, then we can record its spectrum in the lab here on Earth, and then finally we look for that spectrum in space using telescopes.”

Searching for molecules in space

The McGuire Group has recently begun to utilize machine learning to suggest good target molecules to search for. In 2023, one of these machine learning models suggested the researchers target a molecule known as 2-methoxyethanol. 

“There are a number of ‘methoxy’ molecules in space, like dimethyl ether, methoxymethanol, ethyl methyl ether, and methyl formate, but 2-methoxyethanol would be the largest and most complex ever seen,” says Fried. To detect this molecule using radiotelescope observations, the group first needed to measure and analyze its rotational spectrum on Earth. The researchers combined experiments from the University of Lille (Lille, France), the New College of Florida (Sarasota, Florida), and the McGuire lab at MIT to measure this spectrum over a broadband region of frequencies ranging from the microwave to sub-millimeter wave regimes (approximately 8 to 500 gigahertz). 

The data gleaned from these measurements permitted a search for the molecule using Atacama Large Millimeter/submillimeter Array (ALMA) observations toward two separate star-forming regions: NGC 6334I and IRAS 16293-2422B. Members of the McGuire group analyzed these telescope observations alongside researchers at the National Radio Astronomy Observatory (Charlottesville, Virginia) and the University of Copenhagen, Denmark. 

“Ultimately, we observed 25 rotational lines of 2-methoxyethanol that lined up with the molecular signal observed toward NGC 6334I (the barcode matched!), thus resulting in a secure detection of 2-methoxyethanol in this source,” says Fried. “This allowed us to then derive physical parameters of the molecule toward NGC 6334I, such as its abundance and excitation temperature. It also enabled an investigation of the possible chemical formation pathways from known interstellar precursors.”

Looking forward

Molecular discoveries like this one help the researchers to better understand the development of molecular complexity in space during the star formation process. 2-methoxyethanol, which contains 13 atoms, is quite large for interstellar standards — as of 2021, only six species larger than 13 atoms were detected outside the solar system, many by McGuire’s group, and all of them existing as ringed structures.  

“Continued observations of large molecules and subsequent derivations of their abundances allows us to advance our knowledge of how efficiently large molecules can form and by which specific reactions they may be produced,” says Fried. “Additionally, since we detected this molecule in NGC 6334I but not in IRAS 16293-2422B, we were presented with a unique opportunity to look into how the differing physical conditions of these two sources may be affecting the chemistry that can occur.”