Machine Learning Engineer (Research)
Machine Learning Engineer (Research)

Machine Learning Engineers in our research group advance the frontier of what is possible in human-level Information Extraction, by conducting fundamental research in the areas of: natural language understanding, computer vision, representation learning, and knowledge graphs.
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Responsibilities

Improve the accuracy of existing information extraction systems by advancing the current state-of-the-art
Experiment and validate for production new AI capabilities
Publish papers to share new discoveries with AI community
Implement your cutting edge research in the world’s largest production knowledge graph
Collaborate with other Diffbot researchers as well as external AI labs
Requirements

PhD or MS in Computer Science or equivalent work experience
Published research in areas of Web information extraction, natural language processing, computer vision, entity linking, relation extraction, representation learning, deep learning, knowledge inference, and other related fields
Preferred Skills

Programming ability: Java, Python, C++, CUDA
Experience in writing algorithms for speed and scalability


Perks & benefits for this role

Competitive compensation
100% company sponsored medical, dental and vision insurance
401k with company contribution matching
Free lunches, snacks and beverages
Customized computer setup
Unlimited paid time off
Parental leave
Dog friendly office
Commuter benefits
Ongoing learning through mentorship and education budget
Office setting – right next to downtown Menlo Park and CalTrain
Each employee has his/her own office
Onsite gym + fitness classes (Zumba, HIIT, Yoga, Body Sculpt, Muscle Conditioning, Ujam, Core Blast, and Mixed Fit)
Work remotely when needed and work on a flexible schedule
Opt-in team events and get togethers – BBQs, game nights, poker nights, happy hours, hiking and more
Work with an exceptional team of bright, innovative, fun and ambitious individuals from all around the world
To apply, please submit:

A short self-introduction expressing your interest and above qualifications
A resume

https://ai-jobs.net/job/machine-learning-engineer-research/

https://t.iss.one/ArtificialIntelligenceArticles

Machine Learning Researcher / Computational Neuroscientist


https://jobs.apple.com/en-us/details/200104555/machine-learning-researcher-computational-neuroscientist

https://t.iss.one/ArtificialIntelligenceArticles

Artificial Intelligence Takes On Earthquake Prediction - After successfully predicting laboratory earthquakes, a team of geophysicists has applied a machine learning algorithm to quakes in the Pacific Northwest.
https://www.quantamagazine.org/artificial-intelligence-takes-on-earthquake-prediction-20190919/

"Hierarchical Reinforcement Learning for Open-Domain Dialog"
Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen, Rosalind Picard : https://arxiv.org/abs/1909.07547
Code: https://github.com/natashamjaques/neural_chat
Bots! https://neural.chat/vhrl_techniques/
#MachineLearning #ReinforcementLearning #Transformers

Do no harm: a roadmap for responsible machine learning for health care
https://www.nature.com/articles/s41591-019-0548-6

Deep Learning Pioneer Yoshua Bengio Says AI Is Not Magic And Intel AI Experts Explain Why And How

https://www.forbes.com/sites/gilpress/2019/09/20/deep-learning-pioneer-yoshua-bengio-says-ai-is-not-magic-and-intel-ai-experts-explain-why-and-how/#19bb57b712a6

Large e-retailer image dataset for visual search and product classification. https://arxiv.org/abs/1909.08612

The Disruptions of 5G on Data-driven Technologies and Applications. https://arxiv.org/abs/1909.08096

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. https://arxiv.org/abs/1909.08072

Megatron-LM: Training Multi-Billion Parameter Language Models Using GPU Model Parallelism. https://arxiv.org/abs/1909.08053

A Deep Learning Approach to Data Compression
Blog by Friso Kingma : https://bair.berkeley.edu/blog/2019/09/19/bit-swap/
#ArtificialIntelligence #DeepLearning #MachineLearning

We're thrilled to announce that the Fall 2020 admissions applications are open! We're ready for the next cohort of future Data Scientists! Please click on the links below for more information! The application deadline for the MS Degree is January 22, 2020 and the deadline for the Ph.D. is December 12, 2019.

For MS Degree information please click the link below.:
https://cds.nyu.edu/ms-adm-req/

For Ph.D. information please click the link below:
https://cds.nyu.edu/academics/phd/

ns3-gym: Extending OpenAI Gym for Networking Research
Piotr Gawłowicz and Anatolij Zubow : https://arxiv.org/abs/1810.03943
#OpenAIGym #Networking #Research

Here's a list of 7 top research on arXiV on AI/deep learning for August 2019 as per Daniel Gutierrez

1) A Probabilistic Representation of Deep Learning

Link: https://arxiv.org/pdf/1908.09772v1.pdf

2) Inception-inspired LSTM for Next-frame Video Prediction
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Link: https://arxiv.org/pdf/1909.05622.pdf

3) Systematic Analysis of Image Generation using GANs

Link: https://arxiv.org/ftp/arxiv/papers/1908/1908.11863.pdf
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4) Dynamic Stale Synchronous Parallel Distributed Training for Deep Learning

Link: https://arxiv.org/pdf/1908.11848.pdf

5) Discovering Reliable Correlations in Categorical Data

Link: https://arxiv.org/pdf/1908.11682.pdf

6) Smaller Models, Better Generalization

Link: https://arxiv.org/pdf/1908.11250.pdf

7) An Auto-ML Framework Based on GBDT for Lifelong Learning

Link: https://arxiv.org/pdf/1908.11033.pdf

Source: https://insidebigdata.com/2019/09/18/best-of-arxiv-org-for-ai-machine-learning-and-deep-learning-august-2019/


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Best Practices for Picking a Machine Learning Model
https://www.kaggle.com/lavanyashukla01/picking-the-best-model-a-whirlwind-tour-of-model

A Friendly Introduction to Real-Time Object Detection using the Powerful SlimYOLOv3 Framework
https://www.analyticsvidhya.com/blog/2019/08/introduction-slimyolov3-real-time-object-detection/

Senior Data Scientist – Digital
https://ai-jobs.net/job/senior-data-scientist-digital/