As a Capital One Machine Learning Engineer, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Working within an Agile environment, you’ll serve as a technical lead, providing input into machine learning architectural design decisions, developing and reviewing model and application code, and ensuring high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. You’ll also mentor other engineers and further develop your technical knowledge and skills to keep Capital One at the cutting edge of technology. 

What you’ll do in the role: 

• Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams

• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment 

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications

• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale 

• Construct optimized data pipelines to feed ML models 

• Use programming languages like Python, Scala, or Java 

• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code 

Basic Qualifications :

• Bachelor’s degree. 

• At least 3 years of experience designing and building data-intensive solutions using distributed computing 

• At least 4 years of experience programming with Python, Scala, or Java

• At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) 

• At least 1 year of experience productionizing, monitoring, and maintaining models 

Preferred Qualifications:

• 1+ years of experience building, scaling, and optimizing ML systems

• 1+ years of experience with data gathering and preparation for ML models

• 2+ years of experience developing performant, resilient, and maintainable code

• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 

• 3+ years of experience with distributed file systems or multi-node database paradigms

• Contributed to open source ML software 

• Authored/co-authored a paper on a ML technique, model, or proof of concept

• 3+ years of experience building production-ready data pipelines that feed ML models 

• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance 

As a Capital One Machine Learning Engineer, you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. Working within an Agile environment, you’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering to keep Capital One at the cutting edge of technology.  

What you’ll do in the role: 

• Deliver ML software models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams

• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment 

• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art, next generation big data and machine learning applications

• Leverage cloud-based architectures and technologies to deliver optimized ML models at scale 

• Construct optimized data pipelines to feed ML models 

• Use programming languages like Python, Scala, or Java 

• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code 

Basic Qualifications:

• Bachelor’s degree 

• At least 2 years of experience designing and building data-intensive solutions using distributed computing

• At least 2 years of experience programming with Python, Scala, or Java 

• At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) 

Preferred Qualifications 

• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 

• 1+ years of experience working with large code bases in a team environment

• 1+ years of experience with distributed file systems or multi-node database paradigms 

• Contributed to open source ML software

• 1+ years of experience building production-ready data pipelines that feed ML models

Make a meaningful impact
Make a positive contribution to hospitals and patients through AI.

Learn and Master
The opportunity to work with, learn from and share knowledge with uber- smart colleagues in a culture of collaboration and technical excellence. We groom our employees and make sure that they stay at the cutting edge of the technology stack.

Performance Incentives
Competitive pay with share award for top performers.

Progression Path
Well-defined tech career progression path

Who Will Impress Us

A strong technical individual with a geeky background like computer science, physics, mathematics who loves programming, solves tough problems, fascinated by Maths and Physics and has a burning desire to build machine learning models.

Machine learning background is not a requirement.

The Candidate

Our aim is to align you with the activities which truly interests you, stretches you technically and helps you grow and impact on billions of patients.

Some of the things you will learn:

Innovate novel models that solve real world problems in the healthcare domain

The models can be forecasting, generative, discriminative, autoregressive, regressive and/or a combination of the above

Work on huge medical datasets from CT, MRI, PET-CT, SPECT-CT, Ultra-sound, X-Ray, Biopsy and many others that encompass over 50 medical disciplines.
Collaborate with the best data scientists in the region, top medical practitioners from prestigious hospitals and top deep learning researchers and advisors from around the world including Harvard and MIT.

Ample research and publication opportunities in the widely coveted arena where AI intersects healthcare.

Desired Education

Bachelors or Masters in Engineering, Computer Science, Mathematics or Physics

Place of Workplace:
Singapore

About Us

BioMind is an award-winning deep technology company focusing on healthcare solutions. We build state-of-the-art Artificial Intelligence (AI) technologies to help hospitals diagnose medical conditions and manage healthcare-related problems. We have a strong team of deep learning scientists, software engineers, medical experts and distinguished advisors from prestigious hospitals and universities. We won the highest Gold award for Techblazer Award 2019 and the winner for APICTA Award 2019 (ICT and Security category), the highest accolade for ICT innovation both at national level and Asia Pacific level respectively.

Make a meaningful impact

Make a positive contribution to hospitals and patients through AI.

Learn and Master

The opportunity to work with, learn from and share knowledge with uber- smart colleagues in a culture of collaboration and technical excellence. We groom our employees and make sure that they stay at the cutting edge of the technology stack.

Progression Path

Well-defined tech career progression path

We are willing to groom engineers and fresh graduates who don’t have a background in deep learning but are hungry to learn. You will also have the opportunities to attend top machine learning conferences like NIPS and ICML.

Who Will Impress Us

A strong technical individual with a geeky background like computer science, physics, mathematics who loves programming, solves tough problems, fascinated by Maths and Physics and wants to learn Artificial Intelligence and build deep learning models.

Machine learning background is not a requirement.

Some of the things you will learn:

• Computer Vision / Image Segmentation, Localisation, Classification
• Deep Learning Techniques, Research Techniques, Paper Writing
• Tensor Flow or Theano or Torch
• Python, C++ or Java
• Numpy, Pandas, Sklearn, Scipy, Seaborn
• Building Deep Learning Models like RNN and CNN and Other Neural Network Models

Desired Education

Bachelor / Master / PhD in Engineering, Computer Science, Mathematics, Physics

Place of Workplace:
Singapore

The Machine Learning Department in Princeton, NJ, has openings for researchers with a passion for developing the next generation of machine intelligence. Expertise in machine learning with a proven track record of original research as well as a keen sense for developing practical applications are prerequisites for this position.

The Machine Learning Department has been at the forefront of research in such areas as deep learning, support vector machines, and semantic analysis for almost two decades. Many technologies developed in our group have been released as innovative products and services of NEC, such as systems for recruiting, surveillance, inspection of manufactured goods, and digital pathology. In addition to contributing to NEC’s business, our research is published in premier venues. Among the challenges we are tackling now are, how to move machine learning to more abstract reasoning, and how this can enable new applications in smart manufacturing, safe cities, and personalized heath care.
http://www.nec-labs.com/research-departments/machine-learning/machine-learning-home

Requirements

• PhD in computer science, statistics, or equivalent
• Research experience in machine learning with strong publication record
• Strong algorithm and numeric computation background
• Programming experience in Python, Lua, C++, or other languages
• Experience with deep learning libraries and platforms a plus, e.g. PyTorch, TensorFlow, or Caffe

For more information about NEC Labs, please access http://www.nec-labs.com/, and submit your CV and research statement through our career center at https://www.appone.com/MainInfoReq.asp?R_ID=3206183.

Equal Opportunity Employer

The Media Analytics Department is seeking outstanding researchers with backgrounds in computer vision or machine learning. Candidates must possess an exceptional track record of original research and passion to create high impact products. Our researchers are expected to establish global leadership in their communities.

NEC Labs provides a vibrant research environment and the Media Analytics team publishes extensively at top-tier venues such as CVPR, ICCV or ECCV. Our key research areas include 3D scene understanding, representation learning and privacy. We are located in San Jose, with a strong internship program and active collaborations with academia. To check out our latest work, please visit: https://bit.ly/39VHNxa.

• PhD in Computer Science (or equivalent)
• Strong publication record at top-tier computer vision or machine learning venues
• Motivation to conduct independent research from conception to implementation
• Programming skills in Python, C or C++

For more information about NEC Labs, please access http://www.nec-labs.com/, and submit your CV and research statement through our career center at https://www.appone.com/MainInfoReq.asp?R_ID=3153152.

Equal Opportunity Employer

The Machine Learning Department of NEC Labs America invites applications for summer and fall 2021 internships.  We have research projects covering many areas of machine learning. The internship will involve research and development of novel machine learning algorithms with applications in image/video analysis, natural language processing, big data analytics, bioinformatics, and health care. Our internships normally result in high-quality publications. Minimum duration of the internships are usually 3 months and the exact dates are flexible.

The Machine Learning group (located at Princeton, NJ) conducts research on various aspects of machine intelligence and reasoning, from the exploration of new algorithms to applications in computer vision, semantic comprehension, and bioinformatics. Our researchers have extensive expertise in theoretical and application aspects of machine learning, as well as in the development of parallel algorithms for large-scale data analysis.

Ongoing projects focus on text understanding, machine reasoning, deep generative models, robust representation learning, few-shot/zero-shot learning, interpretable models, data visualization, deep learning systems, and deep reinforcement learning, among others. Publishing is an integral part of our activities as a means for calibrating the quality of the research and to ensure staying at the forefront of technology. Application projects emphasize technologies that solve real world problems, and many of our research results have been and will be transferred into industry products.

Requirements:

• Currently enrolled in PhD/MSc program in computer science, statistics, electrical engineering, computational biology, or equivalent.
• Research experience in machine learning.
• Strong computational background.
• Strong programming and scripting skills.
• Strong communication and collaboration skills.

For more information about NEC Labs, please access http://www.nec-labs.com/, and submit your CV and research statement through our career center at:  https://www.appone.com/MainInfoReq.asp?R_ID=3316386.

Equal Opportunity Employer

BioMind is an award-winning Artificial Intelligence (AI) company offering advanced technology solutions in healthcare industry. As the world’s first company to obtain both European CE mark and Singapore HSA medical device certification, we pride ourselves in empowering the healthcare community through deep technology. Driven by a large team of machine learning engineers, regulatory experts, and medical professionals from prestigious hospitals, we envision to scale healthcare expertise globally using AI. BioMind has also been crowned the Champion in both the Techblazer Award 2019 and 19th Asia Pacific ICT Alliance Award. These highest accolades both nationally and internationally for ICT innovation are strong endorsements of how our technology can deliver unprecedented benefits to people.
 

What are we looking for

A strong technical guy with a geeky background like Computer Science, Physics, Mathematics who loves programming, solves tough problems, fascinated by Math and Physics and wants to learn artificial intelligence and build deep learning models. Machine learning background is not a requirement.

The Candidate

Our aim is to align you with the activities which truly interest you; will stretch you technically; help you grow and impact on billions of patients.

Some of the things you will learn

• Computer Vision / Image Segmentation, Localization, Classification
• Deep Learning Techniques, Research Techniques, Paper Writing
• Deep learning tools: TensorFlow, NumPy, Pandas, Sklearn, SciPy, Seaborn
• Building deep learning models, understanding the learning mechanisms
• Learning from professors from MIT, NUS, Tsinghua
• Interacting with top neurologists and doctors

Education

Bachelor / Master / PhD in Engineering or Computer Science or Mathematics or Physics.

We can offer you

• Master, Teach, learn – The opportunity to work with, learn from and share knowledge with ultra-smart colleagues in a culture of collaboration and technical excellence. We groom our employees and make sure that they stay at the cutting edge of the technology stack.
• Impact – Huge potential to make a positive contribution across our business, people, and partners
• Remuneration – Competitive pay with share award for top performers.

We are willing to groom engineers and fresh graduates who do not have a background in deep learning but are interested to learn. You will also have the opportunity to attend top machine learning conferences like NIPS and ICML.

Location

Beijing

Contact Info

HR: WANG Hao, +86 13161375845, hao.wang@biomind.ai