Interesting Data Gigs # 41: 7 Jobs, 7 Ideas

Open roles at Atlassian,, Cohere, Wefox, Snowflake, Adobe and Ampere Computing

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7 Jobs, 7 Ideas

1. Product Manager - AI and Machine Learning at Adobe: Listen/Watch the podcast episode of Lenny’s Podcast with Scott Belsky (Chief Strategy Officer and EVP of Design and Emerging Products at Adobe), make sure to answer the favorite questions from Scott in the episode on paper

3. Senior Data Engineer at Atlassian: Take some ideas from this tweet from Jamin Ball and build your own data visualization to see the profitability trends for $TEAM (stock symbol for Atlassian)

5. Business Data Analyst at Monday: Analyze the last financial report from the company, and bring some conclusions to the interviews. Start with my favorite slide of the presentation Q1 2023 Investors Presentation

Why? Because I share a lot of ARM-focused news. In the last issue # 37, I shared that Ampere Computing launched a new cloud-native processor family called AmpereOne.

Frederic Lardinois wrote a very good article detailing the launch, and my favorite part of it was this one:

These processors remain compatible with the Arm instruction set, so there’s nothing new developers have to do to support them, but more importantly, by designing its own cores, Ampere was able to optimize these processors for its core user base of large cloud platforms. The new AmpereOne chips can support up to 192 cores, a significant upgrade from the Altra Max chips’ maximum of 128. In the AmpereOne family, every core now also gets 2MB of L2 private cache (up from 1MB) and the company added several features that ensure that every core gets access to the same amount of memory bandwidth (or not, if that’s what the user desires) and provide more fine-grained power management, for example. There are also features like process aging monitoring, which helps these vendors better manage the lifecycle of the processor and monitor it for issues, as well as advanced droop detection and security features like memory tagging and single-key memory encryption.

Frederic Lardinois from TechCrunch

If you need more for your research, I encourage you to add this other article to your arsenal:

7. Member of Technical Staff, Data Acquisition at Cohere: Read very closely the description because this role is critical for Cohere:

At Cohere, we strive to continually improve our large language models. Data acquisition is crucial for the sucess of our business. Our ability to responsibly acquire data that is accurate, relevant, and timely is key to our ability to improve the quality of our models. We strive to continuously improve our data acquisition processes and systems to ensure that we have the data we need to stay competitive and meet the needs of our customers.

We are looking for a Member of Technical Staff, Data Acquisition to join our team. This role would be part of the Data Acquisition team, which broadly provides data for training models at Cohere and is responsible for building and maintaining the infrastructure that acquires, cleans, and formats data for model training. The main responsibility of this role is to improve our internal data acquisition infrastructure, which includes data crawlers, formatters, and integrations with data providers. This role would also work closely with different teams at Cohere to support their data acquisition needs, as well as engage in more experimental work to develop highly informative data signals.


Make sure to read this paper first, and then everything you can about Large Languages Models

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