princehonest

Let's say you had a hardware budget of $5,000. What machine would you buy or build to run Devstral Small 2? The HuggingFace page claims it can run on a Mac with 32 GB of memory or an RTX 4090. What kind of tokens per second would you get on each? What about DGX Spark? What about RTX 5090 or Pro series? What about external GPUs on Oculink with a mini PC?

It would be great if the meals had macros per serving listed, total calories, protein, carbs (+ fiber), fat per serving.

Edit: I see there is a nutrition facts button.

Is there a button I can press that says "suggest meals with more protein per serving"?

Pinecone | Software Engineer: Full-Stack Frontend | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/a6f4b3203us

Pinecone (https://www.pinecone.io/) is building similarity search at scale, providing vector indexing as a service. We're a distributed team with offices in New York, San Mateo, and Tel Aviv. At Pinecone you will work with world-class scientists and engineers who have built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: https://grnh.se/a6f4b3203us

Pinecone | Software Engineer: Distributed Data Systems, Infrastructure & Tools, Full-Stack Frontend; SRE | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/a6f4b3203us

Pinecone (https://www.pinecone.io/) is building similarity search at scale, providing vector indexing as a service. We're a distributed team with offices in New York, San Mateo, and Tel Aviv. At Pinecone you will work with world-class scientists and engineers who have built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: https://grnh.se/a6f4b3203us

Pinecone | Software Engineer: Distributed Data Systems, Infrastructure & Tools, Frontend; SRE | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/a6f4b3203us

Pinecone (https://www.pinecone.io/) is building a vector database for machine learning applications. We're a distributed team with offices in New York, San Mateo, and Tel Aviv. At Pinecone you will work with world-class scientists and engineers who have built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: https://grnh.se/a6f4b3203us

Pinecone | Software Engineer: Distributed Data Systems, Infrastructure & Tools, Frontend | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/a6f4b3203us

Pinecone (https://www.pinecone.io/) is building a vector database for machine learning applications. We're a distributed team with offices in New York, San Mateo, and Tel Aviv. At Pinecone you will work with world-class scientists and engineers who have built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: https://grnh.se/a6f4b3203us

Pinecone | Software Engineer: Distributed Data Systems, Distributed ML Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/a6f4b3203us

Pinecone is pioneering a vector database for AI/ML applications. We provide customers with search and recommendation capabilities that until now have been in the hands of a few large tech giants. Our team includes founders of multiple startups, CS professors, and world-class engineers formerly from Amazon, Google & Facebook.

If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, if you like moving fast, and feel restless when a day goes by without attaining something impactful, it’s a opportunity to join an exciting startup as one of the first employees.

Apply here: https://grnh.se/a6f4b3203us

P.S. Visit https://www.pinecone.io/ to apply for early access to our upcoming launch.

HyperCube | Software Engineer: Distributed Data Systems, Distributed ML Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://www.hypercube.ai/openings/

HyperCube is pioneering a Deep Learning database. We provide customers with DL search, recommendation, and personalization capabilities that until now have been in the hands of a few large tech giants. Our team includes founders of multiple startups, CS professors, and world-class engineers formerly from Amazon, Google & Facebook.

If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, if you like moving fast, and feel restless when a day goes by without attaining something impactful, it’s an opportunity to join an exciting startup as one of the first employees.

Our current tech stack includes Python, C++, Kubernetes, AWS.

Apply here: https://www.hypercube.ai/openings/

HyperCube | Software Engineer: Distributed Data Systems, Distributed ML Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://www.hypercube.ai/openings/

HyperCube is pioneering a Deep Learning database. We provide customers with DL search, recommendation, and personalization capabilities that until now have been in the hands of a few large tech giants. Our team includes founders of multiple startups, CS professors, and world-class engineers formerly from Amazon, Google & Facebook.

If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, if you like moving fast, and feel restless when a day goes by without attaining something impactful, it’s a opportunity to join an exciting startup as one of the first employees.

Our current tech stack includes Python, C++, Kubernetes, AWS.

Apply here: https://www.hypercube.ai/openings/

HyperCube | Software Engineer: Distributed Data Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/7bf4a2f63us

HyperCube is pioneering a Deep Learning platform for information retrieval. We provide customers with DL search, recommendation, and personalization capabilities that until now have been in the hands of a few large tech giants. Our team includes founders of multiple startups, CS professors, and world-class engineers formerly from Amazon, Google & Facebook.

We’re looking for a distributed systems engineer who is an expert of database internals, and well-versed in information retrieval.

If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, if you like moving fast, and feel restless when a day goes by without attaining something impactful, it’s an opportunity to join an exciting startup as one of the early employees.

You should have:

* At least 4 years of experience as a Software Engineer

* Extensive experience in database internals and information retrieval

* Experience in building web-scale services and distributed systems

* Proficiency in at least one scripting language, such as Python

* Proficiency in at least one compiled language, such as C++

While not necessary, it would also help to have experience with either embeddings, nearest-neighbor search, productionizing ML models, or DL frameworks (such as TensorFlow, PyTorch).

Apply here: (NYC) https://grnh.se/7bf4a2f63us (SF Bay Area): https://grnh.se/8af359d63us (Tel Aviv): https://grnh.se/ef65badd3us

HyperCube | Software Engineer: Distributed Data Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/7bf4a2f63us

HyperCube is pioneering a Deep Learning platform for information retrieval. We provide customers with DL search, recommendation, and personalization capabilities that until now have been in the hands of a few large tech giants. Our team includes founders of multiple startups, CS professors, and world-class engineers formerly from Amazon, Google & Facebook.

We’re looking for a distributed systems engineer who is an expert of database internals, and well-versed in information retrieval.

If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, if you like moving fast, and feel restless when a day goes by without attaining something impactful, it’s an opportunity to join an exciting startup as one of the early employees.

You should have:

* At least 4 years of experience as a Software Engineer

* Extensive experience in database internals and information retrieval

* Experience in building web-scale services and distributed systems

* Proficiency in at least one scripting language, such as Python, Scala

* Proficiency in at least one compiled language, such as C++, Go, Java

While not necessary, it would also help to have experience with either embeddings, nearest-neighbor search, productionizing ML models, or DL frameworks (such as TensorFlow, PyTorch).

Apply here: (NYC) https://grnh.se/7bf4a2f63us (SF Bay Area): https://grnh.se/8af359d63us (Tel Aviv): https://grnh.se/ef65badd3us

HyperCube | Software Engineer: Distributed Data Systems | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/7bf4a2f63us

HyperCube is pioneering a Deep Learning platform for information retrieval. We provide customers with DL search, recommendation, and personalization capabilities that until now have been in the hands of a few large tech giants. By pushing the boundaries of science and technology, HyperCube transforms data and models into a powerful serving engine that is delightful to use at any scale. If you’re excited about hard problems at the intersection of AI/ML, search engines, and databases, we would love to meet you. If you’re a builder of products and of teams, and feel restless when a day goes by without attaining something impactful, come join us. Our team includes founders of multiple startups, CS professors, and world-class scientists and engineers.

As a Software Engineer: Distributed Data Systems, you will lead, architect, build and maintain large scale distributed data systems; manage cloud based services; tackle challenging algorithmic problems in a fast-paced environment; experiment with and benchmark various solutions; present results at technical conferences; improve the team by introducing new tools and best practices; drive the standards around our code and architecture; and attract, excite and mentor best-in-class engineers.

Our current tech stack includes AWS, Kubernetes, Python, C++.

You should have:

* At least six years of experience as a Software Engineer

* Proficiency in at least one scripting language, such as Python, Scala

* Proficiency in at least one compiled language, such as C++, Go, Java

* Experience in building web-scale services and distributed systems

* Experience in information retrieval, such as Lucene, Elasticsearch, database internals, etc

Apply here: (NYC) https://grnh.se/7bf4a2f63us (SF Bay Area): https://grnh.se/8af359d63us (Tel Aviv): https://grnh.se/ef65badd3us

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/7bf4a2f63us

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

Required experience

- We are looking for software engineers with at least 3 years of experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

Our current tech stack: AWS, Kubernetes, Python, C++. HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: (NYC) https://grnh.se/7bf4a2f63us

(SF Bay Area): https://grnh.se/8af359d63us

(Tel Aviv): https://grnh.se/ef65badd3us

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/7bf4a2f63us

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

Required experience

- We are looking for software engineers with at least 3 years of experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

Our current tech stack: AWS, Kubernetes, Python, C++.

HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: (NYC) https://grnh.se/7bf4a2f63us (SF Bay Area): https://grnh.se/8af359d63us (Tel Aviv): https://grnh.se/ef65badd3us

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://grnh.se/8cc92a153us

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

Required experience

- We are looking for software engineers with at least 2 years of experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

Our current tech stack: AWS, Kubernetes, Python, C++.

HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Apply here: https://grnh.se/8cc92a153us

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://www.hypercube.ai

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

Required experience

- We are looking for software engineers with at least 2 years of experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

Our current tech stack: AWS, Kubernetes, Python, C++.

HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Email amir [ at ] hypercube.ai, subject line "Hacker News April 2020", to apply or learn more.

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://www.hypercube.ai

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

We are looking for a software engineer with at least 2 years of experience.

Our current tech stack: AWS, Kubernetes, Python, C++.

Required experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

Email amir [ at ] hypercube.ai, subject line "Hacker News March 2020", to apply or learn more.

I appreciate your humility. I still encourage you to apply.

Please e-mail me your CV (address in original post). We may consider exceptional candidates for remote work.

HyperCube | Software Engineer | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | Full-time | https://www.hypercube.ai

Do you want to work on challenging machine learning and distributed systems problems? HyperCube is a real-time serving engine for deep learning retrieval applications.

We are looking for a software engineer with at least 2 years of experience.

Our current tech stack: AWS, Kubernetes, Python, C++.

Required experience

- At least one scripting language, such as Python, Scala, etc.

- At least one compiled language, such as C++, Go, Java, etc.

Preferred experience, 2 or more of the following:

- At least one deep learning framework, such as Tensorflow, PyTorch, MXNet, etc.

- Building web-scale services and/or distributed systems

- Productionizing machine learning models and applications

- Embeddings and nearest-neighbor search algorithms

- Information retrieval (i.e. Lucene, Elasticsearch, database internals, etc.)

- Hardware acceleration (CPU, GPU, TPU, FPGA, etc.)

HyperCube is a distributed team with offices in New York, NY, San Mateo, CA, and Tel Aviv, Israel. Our team includes world-class scientists and engineers who built large scale ML applications and platforms (including Amazon SageMaker) at leading companies and cloud providers. We are passionate about building great solutions by pushing the boundaries of science and technology.

amir [ at ] hypercube.ai, subject line "Hacker News February 2020", to apply or learn more.

HyperCube | Research Engineer, Applied Scientist, Product Manager | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | https://www.hypercubesystems.com

HyperCube develops a high-performance enterprise platform for deploying machine learning and artificial intelligence applications. The nature of our product is such that our technical staff must be technically outstanding, scientifically grounded, and customer outcome driven.

Learn more about our research engineering (http://bit.ly/2JGaDFW), applied science (http://bit.ly/325ychU), and product management roles (http://bit.ly/2px3Mru). Apply by sending your resume to jobs@hypercubesystems.com, subject line "Hacker News November 2019".

HyperCube | New York, NY (NYC) & San Francisco Bay Area, CA (SF) & Tel Aviv, Israel | http://bit.ly/2ohHLMs

HyperCube develops a high-performance enterprise platform for deploying machine learning and artificial intelligence applications. The nature of our product is such that our technical staff must be technically outstanding, scientifically grounded, and customer outcome driven. We're currently hiring research engineers and applied scientists. Apply here: http://bit.ly/2ohHLMs

HyperCube | New York, NY (NYC) & San Francisco, CA (SF) | http://bit.ly/2lviMnm

HyperCube develops a high-performance enterprise platform for deploying machine learning and artificial intelligence applications. The nature of our product is such that our technical staff must be technically outstanding, scientifically grounded, and customer outcome driven.

We're currently hiring research engineers, applied scientists, and product managers. Apply here: http://bit.ly/2lviMnm

I've been considering writing my own puppeteer docker image such that one could freeze the image at crawl time after a page has loaded. This would allow me to re-write the page-parsing logic after the page layout changes. Has anyone done this already or know of any other efforts to serialize the puppeteer page object to handle parsing bugs?

After a weekend of searching, I wasn't able to find it so I built one myself. Check it out here: http://cfsheet.launchrock.com/

In office and working remotely will never be the same experience. I worked remotely for three years at my previous job, where I was part of a team of a dozen or so that was headquartered in a central location. The majority of the team participated at the HQ, and I was remote. We had IRC, video conferencing, and all the necessary technology set up. Regular visits to HQ helped. However, the thing that made the biggest impact was everyone else on the team started to work from home on occasion. This made communication happen in a remote-first manner so it was level playing field for all members. I would suggest reading the book, Remote, for more ideas of how to make it work.

"Please do not put solutions to exercises online as it is important for students to work out solutions for themselves rather than copy them from the internet."

I find crowdsourced solutions for honest autodidacts very valuable.

A user could be any business with a software-fixable problem they would be willing to pay for. I don't think the size or stage of the business has to qualify them.

SEEKING WORK - Austin or remote - me@princehonest.com

I'm a software engineer with a background in cloud computing and financial trading looking for part-time projects in the field of data science and engineering. My current skillset is in R, Python, C/C++ in a Linux environment.

SEEKING WORK - Austin or remote - amir.sadoughi+hn@gmail.com

I'm a software engineer with a background in cloud computing and financial trading looking for part-time projects in the field of data science and engineering.

My current skillset is in R, Python, C/C++ in a Linux environment. My most recent accomplishment has been completing Stanford's Statistical Learning MOOC. I've curated and mostly wrote the unofficial community solutions guide: https://github.com/asadoughi/stat-learning