Facebook AI Research Least Requisite To Hire Machine Learning, Engineers

Facebook is all set to double the size of the Facebook AI Research (FAIR) division in the upcoming two years, according to the latest report issued by the company’s chief AI scientist, Yann LeCun.

Facebook AI Research is one of the leading company in the field of AI. Its primary focus is to understand and develop systems based on AI technology in order to solve mankind problems.



FAIR has currently 180-200 staff. If we look at the growth graph of Facebook AI Research then it’s pretty clear that the division is definitely going to receive a growth around 400 people by 2020 as Facebook continues to put AI at the heart of its platforms.

If you are the one who wants to get hired in big AI companies and want to work with big and smart people then this is your opportunity, Facebook AI Research is one of the best places that can turn you into a gigantic ocean of knowledge and experience.




In this post, we will discuss what are the minimum requirements to get hired in Facebook AI Research (FAIR). We will focus on mainly:-

1) Software Engineer, Machine Learning,

2)  Instagram – Software Engineer,

3) Machine Learning Engineer, Oculus,

4) Machine Learning, Machine Learning Engineer (Conversational AI Group),

5) Machine Learning Engineers – Integrity and Anti-Abuse,

6) Applied Research Scientist, Core Machine Learning,

7) Research Scientist – Applied Machine Learning




Software Engineer, Machine Learning at FAIR

Responsibilities 

1) Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based model

2) Suggest, collect and synthesize requirements and create effective feature roadmap

3) Code deliverables in tandem with the engineering team

4) Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Minimum Qualification

1) Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or artificial intelligence

2) Proven ability to translate insights into business recommendations

3) Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable

4) Expert knowledge developing and debugging in C/C++ and Java

5) Experience with scripting languages such as Perl, Python, PHP, and shell scripts



Preferred Qualification

1) MS degree in Computer Science or related quantitative field with 5+ years of machine learning related work or research, or Ph.D. degree in Computer Science or related quantitative field

2) Experience with filesystems, server architectures, and distributed systems

Apply Now (London, United Kingdom or Go as per you desired loc.)

Instagram – Software Engineer, Machine Learning at FAIR

Responsibilities 

1) Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models

2) Suggest, collect and synthesize requirements and create effective feature roadmap

3) Apply expert software development skills to a wide range of ML-related coding projects

4) Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Minimum Qualification

1) MS degree in Computer Science or related quantitative field with 5+ years of relevant experience or Ph.D. degree in Computer Science or related quantitative field

2) Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, large-scale data mining or artificial intelligence.

3) Proven ability to translate insights into business recommendations

4) Experience with Hadoop/Hbase/Pig or MapReduce/Sawzall/Bigtable

5) Knowledge in developing and debugging in C/C++ and Java

6) Experience with scripting languages such as Perl, Python, PHP, and shell scripts

7) Experience with filesystems, server architectures, and distributed systems

Apply Now (New York or Go as per you desired loc.)




Oculus – Machine Learning Engineer at FAIR

Responsibilities 

1) Design, iterate and fine-tune neural network models.

2) Analyze runtime efficiency and optimal performance/accuracy trade-offs.

3) Profile and optimize the performance of complex ML systems, use cutting edge hardware accelerators.

4) Design and implement ML code on co-processors such as DSPs and CNN engines.

5) Develop optimized software to run on a variety of platforms and environments.

6) Implement an end-to-end framework to search for neural network models with various resource constraints and performance characteristics.

Minimum Qualification

1) M.S. or Ph.D. in Computer Science and 3+ years of work experience in ML software in C++.

2) Experience porting ML algorithms to new hardware/software platforms.

3) Experience optimizing ML software algorithms with hardware acceleration techniques.

4) Experience with vectorization techniques on at least one platform (e.g. SSE, NEON, etc.).

5) Experience with at least one scientific computation package (e.g. Eigen, Toon, etc.).

6) Experience with Software Development processes including source control, bug tracking, and design documentation.

7) Experience with scripting languages such as Python.

Preferred Qualification

1) 5+ years of experience in optimizing machine learning networks techniques on embedded platforms.

2) Experience in designing efficient neural network models and deploying them on mobile platforms.

3) Experience with C++11 / C++14 features and principles.

4) Experience with at least one DSP or CNN engine.

5) Publications at top computer vision and machine learning conference such as CVPR, ECCV, ICCV, ICML, NIPS.

6) Demonstrated ability working collaboratively in cross-functional tea

Apply Now ( Menlo Park, CA or Go as per you desired loc.)

Machine Learning Engineer (Conversational AI Group) at FAIR

Responsibilities 

1) Conduct research to advance the state of the art in neural networks especially in the context of Dialog Systems

2) Utilize that research to develop and deploy scalable neural network models into production to impact billions of people using Facebook

3) Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies

4) Apply expert coding skills to platform development projects in partnership with other engineers

5) Adapt machine learning and neural network algorithms for training competitive, state-of-the-art models while making the best use of modern parallel environments (e.g. distributed clusters, GPU)

Minimum Qualification

1) MS degree in Computer Science or related quantitative field with 5+ years of similar experience, or Ph.D. degree in Computer Science or related quantitative field

2) Knowledge of machine learning and deep learning research

3) Experience building systems based on machine learning and/or deep learning methods

4) Experience in C++ and Python

5) Experience with filesystems, server architectures, and distributed systems

Apply Now ( Seattle, WA or Go as per you desired loc.)

Machine Learning Engineers – Integrity and Anti-Abuse at FAIR

Responsibilities 

1) Develop situational awareness in a highly adversarial environment and keep Facebook’s anti-abuse capabilities ahead of our attackers

2) Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rule-based models

3) Suggest, collect and synthesize requirements and create effective feature roadmap

4) Apply state-of-the-art ML techniques to a broad range of products and use cases

5) Extend state-of-the-art ML on areas such as actor profiling, content understanding (text, image, video, audio, web) as well as new adversarial ML techniques

5) Analyze the latest attacker techniques and apply solutions to detect them holistically and stop them proactively

6) Take a leadership role in driving anti-abuse initiatives across the company

Minimum Qualification

1) MS degree or Ph.D. degree in Computer Science or related quantitative field

2) 3+ years of industrial engineering experience in one or more of the following areas: machine learning, anomaly detection, recommendation systems, pattern recognition, data mining, content understanding or artificial intelligence

3) Experience performing data analysis and translating the results into business recommendations

4) Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable

5) Knowledge developing and debugging in C/C++ and Java

6) Experience with scripting languages such as Perl, Python, PHP, and shell scripts

Apply Now (Seattle, WA or Go as per you desired loc.)

Applied Research Scientist, Core Machine Learning at FAIR

Responsibilities

1) Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies

2) Combine broad and deep knowledge of relevant research domains with the ability to synthesize a wide range of requirements to make significant contributions to the feature roadmap for the applied machine learning platform

3) Apply expert coding skills to platform development projects in partnership with other engineers on ranking and infrastructure teams

4) Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Minimum Qualification

1) MS degree in Computer Science or related quantitative field with 5+ years of relevant experience, or Ph.D. degree in Computer Science or related quantitative field

2) Knowledge of machine learning and deep learning research

3) Experience building systems based on machine learning and/or deep learning methods

3) Knowledge developing and debugging in C/C++, Java, and/or Scala

4) Experience with filesystems, server architectures, and distributed systems

Apply Now (Menlo Park, CANew York or Go as per you desired loc.)

Research Scientist – Applied Machine Learning

Responsibilities 

1) Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies.

2) Combine broad and deep knowledge of relevant research domains with the ability to synthesize a wide range of requirements to make significant contributions to the feature roadmap for the applied machine learning platform.

3) Apply expert coding skills to platform development projects in partnership with other engineers on ranking and infrastructure teams.

4) Adapt machine learning and neural network algorithms and architectures to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).

Minimum Qualification

1) Ph.D. degree in Computer Science or related quantitative field and 3+ years of industry experience.

2) Knowledge of machine learning and deep learning research.

3) Experience building systems based on machine learning and/or deep learning methods.

4) Knowledge developing and debugging in C/C++, Java, and/or Scala.

Apply Now (Redmond, WA or Go as per you desired loc.)

Facebook AI Research is expanding at a great speed, the company has now many labs in areas like Menlo Park, New York, Paris, Montreal, Tel Aviv, Seattle, Pittsburgh, and London. Facebook AI Research has also partnered with academic institutions and published countless papers and studies.

AI has become so central to Facebook that FAIR is now part of a larger Facebook AI organization that works on all aspects of AI R&D, from fundamental research to applied research and technology development.

A significant part of the Facebook AI Research division focuses on fundamental areas like reasoning, prediction, planning, and unsupervised learning.

This year, Facebook AI Research has won recognition, including Best Paper awards, at ACLEMNLPCVPR, and ECCV, and Test of Time awards at ECCVICML, and NeurIPS. We know working in the open allows everyone to make faster progress on AI.

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