Ask HN: Who is hiring? (October 2017)

Skyscanner | full-time, mid to senior various | London, Barcelona, Edinburgh, Glasgow, Budapest, Sofia | ONSITE, VISA http://grnh.se/uvwteh1

We're one of the biggest (and growing) technology-led travel search products in the world. Unbiased and free, we help tens of millions of travelers to see the world every month.

We are hiring at mid to senior level in many disciplines:

    - Full stack, working with React on the frontend. 
 
    - Growth, product and designer roles.  

    - Backend engineers for micro-services and distributed systems.  

    - Data engineering, data science, and machine learning roles.  

    - iOS & Android.

We work with open source technology and have great tooling for: Docker, Java, Python, JavaScript & NodeJS.

I've been at Skyscanner for 1.5 years and I really like working here. You will get lots of freedom and responsbility, and work on solving problems at impressive scale. People are smart and friendly here, and there's always a lot of effort put in to make Skyscanner an even better place to work. If you've got good software industry or tech company experience, know what best practices look like, and have the drive to improve product and people around you: we're interested.

You can click my referral link at the top of this post, or email me: robin.tweedie@skyscanner.net if you would like to be referred or have any questions. Permanent & on-site roles only: relocation and visa assistance for senior roles.

Boston, MA | Sentenai | Full-time | On-site

Apply at: jobs@sentenai.com

Keywords: Haskell, Machine Learning, Distributed Systems, FreeBSD

Sentenai: Machine Intelligence. Accelerated.

Who we’re looking for:

Haskellers with an interest in distributed systems and machine learning. The more production Haskell experience, the better. Applied maths and type theory backgrounds are highly desirable, as is experience with optimizing large in-memory data structures. Our culture is built on a foundation of good communication skills and solid engineering principles. Sentenai has been built with Haskell and running on FreeBSD since day 1, and two years later Sentenai remains committed to Haskell as we grow our engineering team.

Why?

Machine intelligence represents a huge potential breakthrough in many industries, from manufacturing to aircraft maintenance. The problem is that working with sensor data to build predictive applications is a slow, time consuming process fraught with data engineering challenges. At Sentenai, we’re determined to change that.

Sentenai is the first cloud data infrastructure purpose-built for data scientists and machine learning engineers who need to rapidly mine diverse sensor data sets for behavioral patterns and build targeted training sets for predictive models.

At the core of Sentenai is a novel set of distributed machine learning technologies and a distributed time-series query engine that natively understands sensor fusion and cross-stream pattern mining. Applied to our distributed data storage and indexing system, these technologies help Sentenai abstract away the details or data preparation, storage and querying on time series data to provide users with a clean data interface to their data without exposing them to the complexities of the underlying database technologies we develop.

Company details:

Sentenai is based in Cambridge, MA in Central Square. Our founding team has deep experience in the IoT space and our engineering team consists of Haskell engineers with a wide range of experience levels (from two to ten years) and non-computer interests (like travel, euro games, playing music, cooking, and hunting for fine wine). We love open source and conferences/meetups, so you’ll probably see some of us attending various conferences or organizing meetups around our interests. Our investors include funds like Flybridge, Founder Collective, Hyperplane and Project 11.

Sound interesting? Contact us at jobs@sentenai.com.

Convoy | Software Engineers | Seattle, WA | Full-Time | ONSITE

https://convoy.com

Help us optimize trucking and logistics - a $800B industry that still runs on fax machines and phone calls.

We would love more engineers, up and down the stack, and anywhere on the generalist specialist spectrum. We use pretty cutting-edge tech (React, React Native, TypeScript, Node, GraphQL), but we're more interested in engineering chops than any particular tech skills.

I've been here since the beginning (over two years now). The team has grown quickly, but we still have a tight-knit and incredibly smart group of engineers. We have an endless supply of interesting problems including machine learning, service architecture, mobile/desktop/web UX, complicated business modeling, and much more.

Some of our backers include Y Combinator (Continuity Fund), Jeff Bezos, Bill Gates, and Greylock Partners. You can read more about us:

http://www.mosaicventures.com/mosaicblog/2017/7/25/our-inves... https://www.theverge.com/2017/7/26/16027650/convoy-trucking-...

If you're interested in hearing more, reach out and grab coffee with me or one of our other developers. Help us grow an amazing tech team from a very early point in our company's history!

http://jobs.convoy.com

Tapad | Unify Life Across Devices | Onsite: New York, NY or Oslo, Norway | $100K - $160K/YR + Bonus

Tapad is the true cross-device partner. By leveraging the power of our proprietary Tapad Device Graph™, we unify data across all devices to understand the interests, passions and behaviors of the audiences that matter most.

Tapad's Open Source tech stack (below) handle:

30+ PB of Data,

Sub 10 ms response times.

___________________________________________

Distributed Applications... Scala, Python

Distributed Computing... Mesos, Kafka, Zookeeper

Distributed Databases... Aerospike, Cassandra, Vertica

Distributed Analytics... Hadoop (YARN), Spark 2

Distributed Storage... Ceph, Hadoop (HDFS)

Global Networking... VXLAN, BGP, EVPN, VPLS

Here are our open roles in Engineering:

Data Scientist (NYC) - http://grnh.se/6c1pdb1

Site Reliability Engineer (Oslo): http://grnh.se/hadlum1

Senior Software Engineer (NYC): http://grnh.se/5giaqb1

Senior Software Engineer (Oslo): http://grnh.se/v4bnl51

Senior Director, Solutions Engineering (NYC): http://grnh.se/801s3q1

Senior Solutions Engineer (NYC): http://grnh.se/4mxjky1

Summer Internship (NYC): http://grnh.se/l78ofb1

Summer Internship (Oslo): http://grnh.se/6lvijp1

CRITEO (http://labs.criteo.com/) | Paris, France | Full-time ONSITE | Machine Learning Engineer (VISA sponsorship)

• Click prediction: How do you accurately predict if the user will click on an ad in less than a millisecond? Thankfully, you have billions of data points to help you.

• Recommender systems: A standard SVD works well. But what happens when you have to choose the top products amongst hundreds of thousands for every user, 2 billion times per day, in less than 50ms?

• Auction theory: In a second-price auction, the theoretical optimal is to bid the expected value. But what happens when you run 15 billion auctions per day against the same competitors?

• Explore/exploit: It's easy, UCB and Thomson sampling have low regret. But what happens when new products come and go and when each ad displayed changes the reward of each arm?

• Offline testing: You can always compute the classification error on model predicting the probability of a click. But is this really related to the online performance of a new model?

• Optimization: Stochastic gradient descent is great when you have lots of data. But what do you do when all data are not equal and you must distribute the learning over several hundred nodes?

Missions of the team in more details: http://labs.criteo.com/wp-content/uploads/2015/04/Software-E...

Feel free to drop me a line at n.rassam[at]criteo.com