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AI Jobs and Career
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- Full Stack Engineer [$150K-$220K]
- Software Engineer, Tooling & AI Workflow, Contract [$90/hour]
- DevOps Engineer, India, Contract [$90/hour]
- More AI Jobs Opportunitieshere
| Job Title | Status | Pay |
|---|---|---|
| Full-Stack Engineer | Strong match, Full-time | $150K - $220K / year |
| Developer Experience and Productivity Engineer | Pre-qualified, Full-time | $160K - $300K / year |
| Software Engineer - Tooling & AI Workflows (Contract) | Contract | $90 / hour |
| DevOps Engineer (India) | Full-time | $20K - $50K / year |
| Senior Full-Stack Engineer | Full-time | $2.8K - $4K / week |
| Enterprise IT & Cloud Domain Expert - India | Contract | $20 - $30 / hour |
| Senior Software Engineer | Contract | $100 - $200 / hour |
| Senior Software Engineer | Pre-qualified, Full-time | $150K - $300K / year |
| Senior Full-Stack Engineer: Latin America | Full-time | $1.6K - $2.1K / week |
| Software Engineering Expert | Contract | $50 - $150 / hour |
| Generalist Video Annotators | Contract | $45 / hour |
| Generalist Writing Expert | Contract | $45 / hour |
| Editors, Fact Checkers, & Data Quality Reviewers | Contract | $50 - $60 / hour |
| Multilingual Expert | Contract | $54 / hour |
| Mathematics Expert (PhD) | Contract | $60 - $80 / hour |
| Software Engineer - India | Contract | $20 - $45 / hour |
| Physics Expert (PhD) | Contract | $60 - $80 / hour |
| Finance Expert | Contract | $150 / hour |
| Designers | Contract | $50 - $70 / hour |
| Chemistry Expert (PhD) | Contract | $60 - $80 / hour |
What is machine learning and how does Netflix use it for its recommendation engine?
What is an online recommendation engine?
Think about examples of machine learning you may have encountered in the past such as a website like Netflix that recommends what video you may be interested in watching next?
Are the recommendations ever wrong or unfair? We will give an example and explain how this could be addressed.
Machine learning is a field of artificial intelligence that Netflix uses to create its recommendation algorithm. The goal of machine learning is to teach computers to learn from data and make predictions based on that data. To do this, Netflix employs Machine Learning Engineers, Data Scientists, and software developers to design and build algorithms that can automatically improve over time. The Netflix recommendations engine is just one example of how machine learning can be used to improve the user experience. By understanding what users watch and why, the recommendations engine can provide tailored suggestions that help users find new shows and movies to enjoy. Machine learning is also used for other Netflix features, such as predicting which shows a user might be interested in watching next, or detecting inappropriate content. In a world where data is becoming increasingly important, machine learning will continue to play a vital role in helping Netflix deliver a great experience to its users.
Netflix’s recommendation engine is one of the company’s most valuable assets. By using machine learning, Netflix is able to constantly improve its recommendations for each individual user.
Machine learning engineers, data scientists, and developers work together to build and improve the recommendation engine.
- They start by collecting data on what users watch and how they interact with the Netflix interface.
- This data is then used to train machine learning models.
- The models are constantly being tweaked and improved by the team of engineers.
- The goal is to make sure that each user sees recommendations that are highly relevant to their interests.
Thanks to the work of the team, Netflix’s recommendation engine is constantly getting better at understanding each individual user.
How Does It Work?
In short, Netflix’s recommendation algorithm looks at what you’ve watched in the past and then makes recommendations based on that data. But of course, it’s a bit more complicated than that. The algorithm also looks at data from other users with similar watching habits to yours. This allows Netflix to give you more tailored recommendations.
For example, say you’re a big fan of Friends (who isn’t?). The algorithm knows that a lot of Friends fans also like shows like Cheers, Seinfeld, and The Office. So, if you’re ever feeling nostalgic and in the mood for a sitcom marathon, Netflix will be there to help you out.
But That’s Not All…
Not only does the algorithm take into account what you’ve watched in the past, but it also looks at what you’re currently watching. For example, let’s say you’re halfway through Season 2 of Breaking Bad and you decide to take a break for a few days. When you come back and finish Season 2, the algorithm knows that you’re now interested in similar shows like Dexter and The Wire. And voila! Those shows will now be recommended to you.
Of course, the algorithm isn’t perfect. There are always going to be times when it recommends a show or movie that just doesn’t interest you. But hey, that’s why they have the “thumbs up/thumbs down” feature. Just give those shows the old thumbs down and never think about them again! Problem solved.
Another angle :
When it comes to TV and movie recommendations, there are two main types of data that are being collected and analyzed:
1) demographic data
2) viewing data.
Demographic data is information like your age, gender, location, etc. This data is generally used to group people with similar interests together so that they can be served more targeted recommendations. For example, if you’re a 25-year-old female living in Los Angeles, you might be grouped together with other 25-year-old females living in Los Angeles who have similar viewing habits as you.
Viewing data is exactly what it sounds like—it’s information on what TV shows and movies you’ve watched in the past. This data is used to identify patterns in your viewing habits so that the algorithm can make better recommendations on what you might want to watch next. For example, if you’ve watched a lot of romantic comedies in the past, the algorithm might recommend other romantic comedies that you might like based on those patterns.
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Are the Recommendations Ever Wrong or Unfair?
Yes and no. The fact of the matter is that no algorithm is perfect—there will always be some error involved. However, these errors are usually minor and don’t have a major impact on our lives. In fact, we often don’t even notice them!
The bigger issue with machine learning isn’t inaccuracy; it’s bias. Because algorithms are designed by humans, they often contain human biases that can seep into the recommendations they make. For example, a recent study found that Amazon’s algorithms were biased against women authors because the majority of book purchases on the site were made by men. As a result, Amazon’s algorithms were more likely to recommend books written by men over books written by women—regardless of quality or popularity.
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These sorts of biases can have major impacts on our lives because they can dictate what we see and don’t see online. If we’re only seeing content that reflects our own biases back at us, we’re not getting a well-rounded view of the world—and that can have serious implications for both our personal lives and society as a whole.
One of the benefits of machine learning is that it can help us make better decisions. For example, if you’re trying to decide what movie to watch on Netflix, the site will use your past viewing history to recommend movies that you might like. This is possible because machine learning algorithms are able to identify patterns in data.
Another benefit of machine learning is that it can help us automate tasks. For example, if you’re a cashier and have to scan the barcodes of the items someone is buying, a machine learning algorithm can be used to automatically scan the barcodes and calculate the total cost of the purchase. This can save time and increase efficiency.
The Consequences of Machine Learning
While machine learning can be beneficial, there are also some potential consequences that should be considered. One consequence is that machine learning algorithms can perpetuate bias. For example, if you’re using a machine learning algorithm to recommend movies to people on Netflix, the algorithm might only recommend movies that are similar to ones that people have already watched. This could lead to people only watching movies that confirm their existing beliefs instead of challenged them.
Another consequence of machine learning is that it can be difficult to understand how the algorithms work. This is because the algorithms are usually created by trained experts and then fine-tuned through trial and error. As a result, regular people often don’t know how or why certain decisions are being made by machines. This lack of transparency can lead to mistrust and frustration.
AI Jobs and Career
And before we wrap up today's AI news, I wanted to share an exciting opportunity for those of you looking to advance your careers in the AI space. You know how rapidly the landscape is evolving, and finding the right fit can be a challenge. That's why I'm excited about Mercor – they're a platform specifically designed to connect top-tier AI talent with leading companies. Whether you're a data scientist, machine learning engineer, or something else entirely, Mercor can help you find your next big role. If you're ready to take the next step in your AI career, check them out through my referral link: https://work.mercor.com/?referralCode=82d5f4e3-e1a3-4064-963f-c197bb2c8db1. It's a fantastic resource, and I encourage you to explore the opportunities they have available.
What are some good datasets for Data Science and Machine Learning?
This scene in the Black Panther trailer, is it T’Challa’s funeral?
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Recommended New Netflix Movies 2022
- Passenger | Official Trailer
by /u/cruelsummerbummer (Movie News and Discussion) on April 14, 2026 at 1:01 pmsubmitted by /u/cruelsummerbummer [link] [comments]
- David Lowery's 'Mother Mary' - Review Thread
by /u/ChiefLeef22 (Movie News and Discussion) on April 14, 2026 at 12:58 pmLong-buried wounds rise to the surface when iconic pop star Mother Mary reunites with her estranged best friend and former costume designer on the eve of her comeback performance. Director: David Lowery Cast: Anne Hathaway, Michaela Coel, Hunter Schafer Rotten Tomatoes: 78% Metacritic: 64 / 100 Some Reviews: Fresh Fiction - Courtney Howard - 5 / 5 As a kissing cousin to SMILE 2 and VOX LUX, MOTHER MARY is wholly unique in its innovative aims. The heady sentiments and haute couture combine in a hallucinatory visual feast. IndieWire - David Ehrlich - 'A-' What happens when two people, or even two sides of the same person, are bound together by a shared feeling of unshakeable absence? The same thing that happened in another of Lowery’s films: They haunt each other to the ends of the earth. Every song becomes a seance, every bump in the night turns into evidence of a specter. Quoth Virginia Woolf: “Whatever hour you woke there was a door shutting.” This beguiling movie flings them back open just as fast, as it explores how art — and maybe art alone — has the power to heal the wounds that can make it hurt so much in the first place. It’s not a ghost story, it’s a resurrection. IGN - Clint Gage - 8 / 10 David Lowery’s latest is a visually fascinating chamber piece with great performances from Anne Hathaway and Michaela Coel. The story of old wounds between former friends and creative partners isn’t the most relatable mannequin on which to assemble a film, so the story of icon Mother Mary and couture designer Sam doesn’t have enough range to carry the film through its final moments. However, everything else, from the sound design to the cinematography and the operatic fantasy of this pop star ghost story (a subgenre I wouldn’t have pegged as “up my alley” but here we are) makes Mother Mary a great piece of art. Next Best Picture - Dan Bayer - 8 / 10 Lowery, clearly fascinated by the plight of the modern pop star, has made “Mother Mary” with both the fervor of a fan and the insight of a fellow artist. The questions the film asks about the identity of pop stars as well as the ownership of their music, their image, and their very souls don’t all have answers, and Lowery doesn’t provide them. He does, however, provide plenty of food for thought as he asks these questions, interrogating the relationship between artists and their audience and what each owes the other. If the surrealism of the film’s last act feels both too much and not enough, at least Lowery dares to take the story in that direction, exploring the spiritual connection between artistic collaborators in an original way. In all the best ways, “Mother Mary” is like a great pop song: Its gleaming surfaces conceal a deeper, darker meaning only discernible through close attention, but that darkness is the magic that keeps you coming back to experience it again and again. CBR - Rachel Leishman - 8 / 10 Mother Mary is, at its core, just a breathtaking showcase of Coel and Hathaway's talent as performers. The two-hander scenes could feel dry and flat but both Coel and Hathaway use the pain of their former friendship to their advantage and makes this duo something absolutely magical. Slant Magazine - Rocco T. Thompson - 3 / 4 Doors are oft-referenced throughout, and the film abounds in images of wounds and penetration, comporting with the central idea that to be creative, to be notable, is to be beatified—a receptacle for the otherworldly. As for if it all hangs together, that’s up to the beholder. A goth-pop memory play, a psychological ghost story, an almost two-hander about the terrors of creative expression—the film is many things, but, above all, it’s an invitation for the pop-loving faithful to commune with something dark and divine. So, open up, and let Mother Mary in. Awards Radar - Joey Magidson - 3 / 4 Mother Mary will confound some, which can come with the Lowery territory, but as long as you allow yourself to drift on to his wavelength, the rewards are certainly there. I was left a bit cold early on by what was unfolding, but especially as the third act began, it all really clicked in for me. Lowery blew me away with A Ghost Story, and while this isn’t on that level (that’s his masterpiece, so far), there are echoes here that I really appreciated. The Wrap - William Bibbiani - 75 / 100 “Mother Mary” takes place in a world where art is magic and forms eternal bonds, which can be a blessing or a curse. It can also raise the dead and infect the soul. And in David Lowery’s film it can captivate the mind even when it’s arguably absurd. We’re watching extremely talented artists try to accomplish something grand and potentially embarrass themselves in the process, and it works because they’re committed to taking that risk. Lowery doesn’t hold back (mostly). His cast doesn’t hold back. That’s how cult classics are born. And let’s face it, cult classics tend to live longer than the bona fide variety, whether they’re brilliant, mortifying, or just plain odd. Variety - Owen Glieberman In “Mother Mary,” the director gives in to that side of himself completely. This is the David Lowery-est David Lowery movie ever made. Which is to say that by the end of it, you may be scratching your head to the point of wanting your money back. Screen Rant - Molly Freeman - 6 / 10 Ultimately, Mother Mary isn't going to be a broad crowd-pleaser – even with its main character taking inspiration from the likes of Lady Gaga and Taylor Swift – but that's okay. With magnificent performances from Hathaway and Coel, stunning and evocative visuals, and a reliance on sensational vibes, Mother Mary is sure to find its fans. Weekend Warrior - Edward Douglas - 5.5/10 Mother Mary is a visually-gorgeous film involving characters who I had a hard time caring about, set in a world of fashion and pop music that I had next to zero interest in. It’s very much a movie made solely for the Coachella crowd, so maybe it will find that audience, but otherwise, there really isn’t much there to recommend. Slash Film - Bill Bria - 5 / 10 "Mother Mary" is unequivocally a gorgeously shot and designed film, so perhaps all of its suggestiveness and symbolism will allow you to open yourself up to it. Sadly, I never felt like I was given the key, so I didn't connect, I could not understand, and I was not entertained. The film is so steeped in ambiguity that it never feels like it reaches confession, nevermind clarity, and yet Lowery and his regular composer Daniel Hart soak the finale in heaps of schmaltz that feels unearned as a result submitted by /u/ChiefLeef22 [link] [comments]
- Netflix playback issueby /u/josh09042 (Netflix) on April 14, 2026 at 12:37 pm
I'm currently watching Monday Night Raw and whenever I fast forward or rewind the timer for the show starts going forward at stupid speeds once I press play It's hard to explain but say I fast forward to 31:00 of the show and start watching, the timer instead of going up in 1 second increments, it starts going in 20 seconds every second so if at any point I fast forward or rewind again or even pause, it's starting from the wrong time So if I want to fast forward a couple minutes, I end up having to rewind more like 10 minutes and then it's all out of sync and often jumps forward 5 minutes anyway from where I pause it (often to even further into the programme than the bugged playback speed had taken it to) Does anyone know what's going on or how to fix it? submitted by /u/josh09042 [link] [comments]
- Bojack Horseman: A Panoramic Spoof of Mankind
by Aslan Flâneur (Netflix on Medium) on April 14, 2026 at 12:28 pmDepression, drugs, celebrity glamour, nihilism and beyond. But the surreal sitcom , which turns 6 today, is so much more than that.Continue reading on Medium »
- Hi reddit! I'm author/actor Ben McKenzie. You may know me from THE OC, GOTHAM, JUNEBUG, SOUTHLAND, BATMAN: YEAR ONE. My directorial debut, EVERYONE IS LYING TO YOU FOR MONEY, is out in theaters this weekend. Ask me anything!
by /u/BenMcKenzieAMA (Movie News and Discussion) on April 14, 2026 at 12:22 pmHi reddit! I'm author/actor Ben McKenzie. You may know me from THE OC, GOTHAM, JUNEBUG, BATMAN: YEAR ONE, SOUTHLAND, and other things. My directorial debut, EVERYONE IS LYING TO YOU FOR MONEY, is based on a book I co-wrote, has played at lots of festivals, and is out in select theaters this weekend. It's a documentary that investigates what's really going on with crypto and the harm it has done to regular people everywhere. Here's our trailer: https://www.youtube.com/watch?v=hEXxAOFqv4U ----------- Directed by: Ben McKenzie Based on the Book: “Easy Money: Cryptocurrency, Casino Capitalism, and the Golden Age of Fraud” by Ben McKenzie & Jacob Silverman Starring: Ben McKenzie, Morena Baccarin, Gerard Butler, Alex Mashinsky, Sam Bankman-Fried, Nayib Bukele Synopsis: Actor and author Ben McKenzie investigates the lies, hype, and harm behind cryptocurrency’s rise – and who’s really paying the price. Distributor: The Forge Release Date: April 17, 2026 Poster: https://i.imgur.com/3mobcVg.jpeg For tickets and more information: everyoneislying.com. ----------- AMA! I'll be answering your questions at 12 PM PT/3 PM ET today. submitted by /u/BenMcKenzieAMA [link] [comments]
- Manosphere Reviewby Jajhar Singh (Netflix on Medium) on April 14, 2026 at 11:53 am
When it comes to mainstream trends more often than not I tend not to be interested. I think it will just pass and become irrelevant again…Continue reading on Medium »
- Cut-out Cut-ups
by Richard Alloway (Netflix on Medium) on April 14, 2026 at 10:57 amContinue reading on Medium »
- Alex Garland’s ‘Elden Ring’ filming in UK for A24, DNA Films; Kit Connor, Cailee Spaeny and Ben Whishaw to star
by /u/EThorns (Movie News and Discussion) on April 14, 2026 at 10:55 amsubmitted by /u/EThorns [link] [comments]
- THE INFINITE CORE BOOK-4 -प्रेम से बंधे, श्राप से शासित
by jig N (Netflix on Medium) on April 14, 2026 at 9:59 amThis book is a work of fiction, born from imagination and created with the intent to inspire, explore, and entertain. The world…Continue reading on Medium »
- The Cleaning Lady: Watching Season 2and Thony Is Testing My Patience.by /u/worrynelly (Netflix) on April 14, 2026 at 9:16 am
I’m deep into Season 2 of The Cleaning Lady, and honestly, Thony is really starting to test my patience. I get that she’s a mom doing whatever it takes to survive, but sometimes it feels like she’s running a one woman “benefits only” program, especially when it comes to Arman. The guy bends over backwards to protect her, take risks, and clean up her messes, yet she rarely seems to return the favor. Instead, Thony charges ahead with decisions that suit her in the moment, leaving Arman to deal with the fallout. Don’t get me wrong, she’s a compelling character and the moral gray areas keep the show interesting, but I can’t help thinking, how many times can Arman stick his neck out before he realizes he deserves better? Anyone else feeling this, or am I being too hard on her? submitted by /u/worrynelly [link] [comments]
- Some anime movies Netflix needs to add!by /u/PotatoFries_1119 (Netflix) on April 14, 2026 at 9:13 am
Petition to make Netflix add some goated anime movies like : Summertime Rendering Summer Ghost The Silent Voice Your lie in April Suzume I want to eat your pancreas The forest of the Fireflies Recommend some more if you guys know some!!!! Netflix Pleaseeee!!!! submitted by /u/PotatoFries_1119 [link] [comments]
- Late Nights, Soft Hearts and Streaming Screens My Honest Take on Netflixby Writershub (Netflix on Medium) on April 14, 2026 at 9:11 am
Some advantages and disadvantages of NetflixContinue reading on Medium »
- Weird recommendationsby /u/Standard_Plum7149 (Netflix) on April 14, 2026 at 9:04 am
NGL sometimes recommendations are weird and tbh I am student that is researching it. Like I am watching something animated like and then boom an adult series that I have no interest of. Here is the survey if you would like to fill out. submitted by /u/Standard_Plum7149 [link] [comments]
- First image of Chris Hemsworth in Matt Ross’ crime thriller ‘KOCKROACH.’ It follows a mysterious stranger who takes on the city’s criminal underworld, transforming himself into a larger-than-life boss.
by /u/chespiotta (Movie News and Discussion) on April 14, 2026 at 8:47 amsubmitted by /u/chespiotta [link] [comments]
- Sony Pictures Boss Tom Rothman Urges Theater Owners to Stop Having 30 Minutes of Trailers and Commercials Before Movies Start:
by /u/tylerthe-theatre (Movie News and Discussion) on April 14, 2026 at 8:16 amsubmitted by /u/tylerthe-theatre [link] [comments]
- All of Us Are Dead Season 2: From School Horror to a Global Outbreak
by Javeria Javed (Netflix on Medium) on April 14, 2026 at 8:04 amWhat happens when a deadly school outbreak turns into a global crisis? All of Us Are Dead Season 2 is set to take the story to a whole new…Continue reading on Medium »
- Why K-Dramas Became a Global Obsession
by Foramgandhi (Netflix on Medium) on April 14, 2026 at 7:32 amThis generation is fast, creative, and always on the move. Sitting still? Almost impossible. They crave something new every second. So…Continue reading on Medium »
- Top Free Netflix Downloaders in 2026: Tested & Reviewed
by Astria (Netflix on Medium) on April 14, 2026 at 6:16 amNetflix is one of the most popular streaming platforms in the world, but sometimes you want to watch your favorite movies and shows…Continue reading on Medium »
- Hold Close What Truly Matters
by Stories by Anwar (Netflix on Medium) on April 14, 2026 at 4:53 amContinue reading on Medium »
- Jumanji 4’ has been officially titled ‘JUMANJI: OPEN WORLD.’
by /u/MoneyLibrarian9032 (Movie News and Discussion) on April 14, 2026 at 3:39 amsubmitted by /u/MoneyLibrarian9032 [link] [comments]
World’s Top 10 Youtube channels in 2022
![r/dataisbeautiful - [OC] World's Top 10 Youtube Channels of 2022](https://preview.redd.it/tu6mde3tkkv91.png?width=960&crop=smart&auto=webp&s=a5c26809a0667101e97db43c0a66006301a1157a)
T-Series, Cocomelon, Set India, PewDiePie, MrBeast, Kids Diana Show, Like Nastya, WWE, Zee Music Company, Vlad and Niki
