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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]
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- 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 |
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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.
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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.
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!
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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.
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.
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.
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.
What are some good datasets for Data Science and Machine Learning?
This scene in the Black Panther trailer, is it T’Challa’s funeral?
Recommended New Netflix Movies 2022
- Return to Silent Hill - Review Thread
by /u/MarvelsGrantMan136 (Movie News and Discussion) on January 21, 2026 at 10:08 pmReturn to Silent Hill - Review Thread Rotten Tomatoes: 9% (11 Reviews) Metacritic: 30 (6 Reviews) Reviews: TotalFilm (1.5/5): Loosely based on the 2001 game Silent Hill 2, Return to Silent Hill can be an atmospheric horror film with original creature designs worthy of Konami's legendary franchise. But a confusing plot, mediocre visual effects, and over-the-top acting might make director Christophe Gans' newest Silent Hill adaptation just as divisive as his first attempt 20 years ago. IGN (50): Return to Silent Hill isn’t the worst entry in this video game movie series, but it fails to accomplish anything that the source material doesn’t do better. The Guardian (2/5): 20 years later, Gans still can’t figure out how to escape the open-ended confinement of gameplay, or even give it the forward momentum of a game with a mission. Slant (12): Christophe Gans’s film does away with all the psychosexual nuance of Silent Hill 2. Collider (3/10): It makes all the sense in the world that fourteen years after Silent Hill: Revelation, the best way to make this movie series relevant again would be to retell the game’s best story, and with the director of the original film. But with bad direction, terrible acting, and a world that has no weight behind it (especially since most of it was clearly made in a computer), this isn’t the way to bring Silent Hill 2 to the big screen. This powerful survival horror story has been turned into an ugly, laughable adaptation that proves that maybe we should’ve never gone back to Silent Hill. The Gamer: Return to Silent Hill isn’t a bad movie. There are still some entertaining moments and scenes of great tension waiting for you. However, this nature of making things more complicated for the sake of it and the lack of nuance left me with a bittersweet taste in my mouth: this should have been a great return for the series to the big screen, and it ended up feeling lukewarm. AwardsWatch (C-): Return to Silent Hill never captures the smothering, oppressive dread of the game, mainly because it’s a property with a premise built on immersion. -------------------- Directed by Christophe Ganz: James is devastated after being separated from his soulmate and receives a mysterious letter that leads him back to a town called Silent Hill, where he hopes to find her. However, he discovers that the town has been changed by some unknown malevolent force and as he delves deeper into the town, he finds terrifying figures, both familiar and unfamiliar. Doubting his mental stability, he tries to comprehend reality and hopes to stay strong enough to rescue his beloved. submitted by /u/MarvelsGrantMan136 [link] [comments]
- Why are the subtitles so goofyby /u/fairplanet (Netflix) on January 21, 2026 at 10:03 pm
So on a chromecast 4th gen i watch with english subtitles since it can be hard to understand it for me some times but when turning it on its really goofy looking Like not just in normal sentence format but diagonally and everything submitted by /u/fairplanet [link] [comments]
- Universal on Netflixby /u/kingcolbe (Netflix) on January 21, 2026 at 9:24 pm
With honey don’t coming to Netflix on February 3rd and Megan 2.0 coming next week is it safe to assume they probably found a way to get out of that Prime Video a couple years early submitted by /u/kingcolbe [link] [comments]
- David Siegel Dies: ‘The Hangover’ Films & ‘Final Destination Bloodlines’ Producer Who Worked On Dozens Of Movies Was 70
by /u/darth_vader39 (Movie News and Discussion) on January 21, 2026 at 8:56 pmsubmitted by /u/darth_vader39 [link] [comments]
- Jason Moore To Direct ‘Murder, She Wrote’ Movie Starring Jamie Lee Curtis For Universal
by /u/TerrifierBlood (Movie News and Discussion) on January 21, 2026 at 8:43 pmsubmitted by /u/TerrifierBlood [link] [comments]
- Anyone try to watch Pulp Fiction on Netflix recently? I just tried, and the picture quality is unwatchable.by /u/HamHamHam2315 (Netflix) on January 21, 2026 at 8:28 pm
I checked my network settings, restarted my router, restarted the Netflix Roku app (twice), checked for updates, and still the picture quality looks like I'm watching it on a VHS copy of a VHS copy of a VHS copy. And it's only Pulp Fiction. Every other thing I just watched was in pristine 4K HD, as expected. Anybody else have this happen with Pulp Fiction? EDIT: It's perfectly fine on my phone. So it's only on my Roku TV, and only Pulp Fiction. Interesting. submitted by /u/HamHamHam2315 [link] [comments]
- Is the Skyscraper live event real or are there precautions we don’t know about?by /u/Timewilltell755 (Netflix) on January 21, 2026 at 8:13 pm
It’s will probably bring in huge ratings but I can’t believe there aren’t any precautions. Is there something Netflix has to sign be absolved of all liability? submitted by /u/Timewilltell755 [link] [comments]
- What movie do you think nailed rainy atmosphere?by /u/yosman88 (Movie News and Discussion) on January 21, 2026 at 7:23 pm
For me its got to be 1998 Godzilla. I dont know why but the rain scenes in the movie felt really authentic. Everyone either looked damp or wet and nailed the atmosphere. I always wondered about the behind the scenes on how they were able to get the shots they did and what was improvised rain and what wasnt. Whats your favorite rainy movie that you felt they nailed? submitted by /u/yosman88 [link] [comments]
- It removed my shows only on my phone and laptop?by /u/St1na_ (Netflix) on January 21, 2026 at 7:08 pm
I was watching Better Call Saul when I noticed my laptops keyboard brightness wasn't working so I downloaded "hp hotkey keyboard " and when i went on netflix the show was suddenly gone? then I entered netflix on my phone and it wouldn't show up there either, but when it use my mobile data it works... does anyone know what to do? it also wont let me watch breaking bad only el camino. if someone knows what error this is please help me. submitted by /u/St1na_ [link] [comments]
- Hello /r/movies! We're Philippa Lowthorpe (director) & Helen Macdonald (author). H IS FOR HAWK, starring Claire Foy & Brendan Gleeson, an adaptation of Helen’s memoir, is out in theaters this week. It's about love, grief, goshawks, and how we lose and find ourselves after loss. Ask us anything!
by /u/HIsForHawkAMA (Movie News and Discussion) on January 21, 2026 at 6:45 pmHello r/movies! We're Philippa (director) and Helen (author), of H IS FOR HAWK. The film premiered at Telluride in August and is out in theaters this Friday 1/23. It stars Claire Foy (as Helen) and Brendan Gleeson. The film is based (and titled) on Helen's memoir. You may also know Philippa for director MISBEHAVIOUR (2020), SWALLOWS AND AMAZONS (2016), THE OTHER BOLEYN GIRL (2003), as well as several episodes of WILLOW, THE CROWN, THE THIRD DAY, PRISONER 951, THREE GIRLS, JAMAICA INN. Full credits here. Synopsis: After losing her beloved father, Helen finds herself saved by an unlikely friendship with a stubborn hawk named Mabel. Trailer: https://www.youtube.com/watch?v=RJ29BBXfN64 Ask us anything! We will be back on Thursday 1/22 at around 3:30 PM ET to answer your questions. submitted by /u/HIsForHawkAMA [link] [comments]
- Official 20th Anniversary Poster for 'Little Miss Sunshine'
by /u/MarvelsGrantMan136 (Movie News and Discussion) on January 21, 2026 at 6:02 pmsubmitted by /u/MarvelsGrantMan136 [link] [comments]
- Batman Movie ‘The Brave and the Bold’ Taps Christina Hodson to Write for DC Studios
by /u/ICumCoffee (Movie News and Discussion) on January 21, 2026 at 5:58 pmsubmitted by /u/ICumCoffee [link] [comments]
- Red Dead Redemption passes 3.3m Netflix downloads while paid game struggles past 10kby /u/-deetjay- (Netflix) on January 21, 2026 at 5:38 pm
submitted by /u/-deetjay- [link] [comments]
- Need calming shows.by /u/Mundane_Main_9616 (Netflix) on January 21, 2026 at 5:23 pm
I need to find a new show that is slightly funny, with very little drama, but still exciting enough to pay attention to in short bursts. I have ADHD and other issues that keep me from paying good attention to TV. So I really don't want something that I have to pay a lot of attention to to understand. I don't like competition shows because of the drama. I need something chill, to not work myself up. I usually can't find a show and sit in silence and it causes racing thoughts or doom scrolling. Any recommendations would be greatly appreciated. submitted by /u/Mundane_Main_9616 [link] [comments]
- New Poster for ‘Nirvana The Band The Show The Movie’ Starring Matt Johnson & Jay McCarrol - When their plan to book a show at the Rivoli goes horribly wrong, Matt and Jay accidentally travel back to the year 2008.
by /u/BunyipPouch (Movie News and Discussion) on January 21, 2026 at 5:08 pmsubmitted by /u/BunyipPouch [link] [comments]
- 'Mercy' - Reviews Discussion Thread | Starring Chris Pratt, Rebecca Fergusonby /u/Opening-Lead5629 (Movie News and Discussion) on January 21, 2026 at 4:58 pm
Reviews are starting to come out for Amazon's 'Mercy'. Lot of people expecting this to be a dud but let's see... I'll update this post with reviews I keep finding. Rotten Tomatoes - 21% Metacritic - 39/100 Reviews: The Independent - 1 / 5 A baffling piece of work that happily swipes the mood and aesthetics of Hollywood’s police state dystopias (Minority Report, RoboCop, Blade Runner etc), while presenting such horrors as an agreeable norm. ThePragueReporter TheGeekTyrant I walked away feeling genuinely entertained and a little impressed. It is not a movie that completely reinvents sci-fi thrillers, but it delivers a tight, engaging ride with strong performances and a concept that keeps your brain busy the entire time. DEADLINE All the technical production elements are first rate, and I guarantee this one will have you on the edge of your seat in its compact running time. It was shot for IMAX, and in a movie all about screens dominating our lives, this one is ideal to be seen on the biggest one of all if you have a chance like I did. The Hollywood Reporter Taking place in real time, Mercy mercifully moves along fairly briskly. But after it’s over you’ll definitely feel the need for a digital detox. While Pratt can be effective in the right vehicle (Jurassic World, Guardians of the Galaxy), he’s very dependent on his athletic physicality. Watching him as he sits motionless in a chair for nearly 90 minutes, not able to resort to the humor with which he often peppers his performances, mainly serves as a demonstration of his limitations as an actor. Ferguson comes off much better, especially when she subtly reveals the hints of emotionality that begin to seep into her character’s data-driven persona. submitted by /u/Opening-Lead5629 [link] [comments]
- In its last season, Stranger Things goes epic but loses something essential
by ajesseswanson (Netflix on Medium) on January 21, 2026 at 4:57 pmWith too many characters and a complex plot to wrap up, Stranger Things spends too much time explaining instead of showing.Continue reading on Medium »
- This Sh??? is like a Movie….
by ragrago (Netflix on Medium) on January 21, 2026 at 4:54 pmThe Americans are behaving as if they already own Greenland. It seems like Trump is always two moves ahead of the EU and one behind Putin…Continue reading on Medium »
- Fitzcarraldo-esque Featsby /u/GenderlyConfusionNow (Movie News and Discussion) on January 21, 2026 at 4:45 pm
I was thinking recently about how mind blowing it is that Werner Herzog actually had people haul the steamboat over the mountain for his movie Fitzcarraldo. I started to wonder what other insane feats have been done for movies. What are real world, practical feats and actions that did not use computers and would be considered above and beyond to get something in camera. submitted by /u/GenderlyConfusionNow [link] [comments]
- Final Oscar Predictions: ‘Sinners,’ ‘One Battle After Another’ and Warner Bros. Poised to Make History and Break Records
by /u/lawrencedun2002 (Movie News and Discussion) on January 21, 2026 at 4:31 pmsubmitted by /u/lawrencedun2002 [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
