דרושים בתחום תפקידים נוספים

The Machine Learning team at JPMorgan Chase combines cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team, and advance the state-of-the-art in financial applications ranging from pricing and credit models to natural language processing. Our work spans the company’s lines of business, with exceptional opportunities in each.

The successful candidate will develop new machine learning methods tailored to banking applications such as risk assessment, trading models, customer relationship management, and pricing models. Machine learning techniques will include feed-forward, recurrent, recursive and convolutional neural networks, maximum entropy models, and other algorithms related to time series analysis and supervised learning. In addition to using and adapting existing models, you will be expected to develop new techniques especially suited to banking applications. The candidate will help in the identification and solution of new problem areas.

Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing and Time Series predictions. Collaborate with all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management.
Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.

MS or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science, or similar BS with 2+ years of experience in a highly quantitative position.
Experience in Deep Learning: DNN, CNN, RNN/LSTM, GAN or other auto encoder (AE).
2+ years of hands-on experience developing machine learning models.
Ability to develop and debug in Python, Java, C or C++. Proficient in git version control. R and Matlab are also relevant.
Extensive experience with machine learning APIs and computational packages (TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels).
Familiarity with basic data table operations (SQL, Hive, etc.)

This position is for someone who can come in and lead AppCard’s Ops team. This person will help influence decisions and lead our entire tech stack on a day to day basis, craft AppCard operational procedures, roll-outs, and SLAs.
If it intrigues you to join a fast-paced startup, using cutting edge technology, then AppCard is the place for you!

Responsibilities:
- Build, rollout and maintain AppCard SLA and operational procedures.
- Collaborate and build strong working relations with all parts of the company.
- Manage AppCard Tiered Operations.
- Establish and lead all operational projects related to security, compliance with regulations and introduction of new tools and capabilities to the AppCard platform.
- Lead AppCard Linux / AWS and Operational IT activities.
- Take part in architecting and integrating auto-scale solutions.
- Improve company remote management and auto-deploy processes.

The DevOps engineer builds tools and critical infrastructures that support the ADM different services mainly in the public cloud. She is a key member of engineering group and aids in deploying shared tools and automation. She will also coach all engineers around automations and Devops. She also supports the already existent automation & deployment in production nowadays.

A typical day in your life in this role:

· You will work closely with other engineers and technical teams in deploying their daily operational support tasks and debugging production issues. The DevOps Engineer performs functions required for the deployment, configuration, support, and troubleshooting of issues with the ADM applications.
· You will regularly checks and monitors the application & automation alerts, diagnoses symptoms, analyses root causes, and deploy preventative measures to avoid reoccurrence of these issues. Operate and maintain services and software solutions.
· Coach other engineers around public cloud and automations.

· Bachelor in Computer Science / Computer Engineering preferred
· CI/CD knowledge (Jenkins, Linux, windows, networking knowledge) and experience working in CD environment (scripting).
· 3 years of previous experience in DevOps world (moving the business forward and giving it a stronger technological advantage).
· Work experience with AWS – A must.
· Work experience with Terraform.
· Experience/ knowledge in the following languages: Python/ Ansible- advantage

About the role:

The DevOps engineer builds tools and critical infrastructures that support the PPM application platforms. He is a key member of engineering group and aids in deploying shared tools and automation. He also supports the already existent automation & deployment in the production.
A typical day in your life in this role:

· You will work closely with other engineering and technical teams in deploying their daily operational support tasks and debugging production issues. The DevOps Engineer performs functions required for the deployment, configuration, support, and troubleshooting of issues with the PPM application.
· You will regularly checks and monitors the application & automation alerts, diagnoses symptoms, analyses root causes, and deploy preventative measures to avoid reoccurrence of these issues. Operate and maintain services and software solutions.

About you/your experience includes:

· Bachelor in Computer Science / Computer Engineering preferred
· CI/CD knowledge (Jenkins, Linux, windows, networking knowledge) and experience working in CD environment (scripting).
· 3 years of previous experience in DevOps world (moving the business forward and giving it a stronger technological advantage).
· Work experience with AWS - Must.
· Work experience with Terraform.
· Experience/ knowledge in the following languages: Python/ Ansible- advantage