Junior Application Engineer - Remote Job, 1+ Year Experience

1 Month ago • 1 Years + • Research & Development • $61,000 PA - $75,000 PA

Job Summary

Job Description

As a Junior Application Engineer at Patterned Learning, you'll work remotely to deliver solutions for Life Sciences customers. Deep LIMS, ELN, and SDMS knowledge is crucial. Responsibilities include developing and deploying solutions, collaborating with customers to understand their needs, configuring Sapio products to meet project criteria (time, budget, quality, and customer success), providing customer training and support, following agile methodologies, documenting feedback, and ensuring issue resolution. You'll work closely with the team and clients to ensure successful project implementation and a positive customer experience.
Must have:
  • 1+ years Life Sciences experience in a lab setting
  • 1+ years configuring LIMS, ELN, or similar software
  • Strong Java programming skills
  • Strong analytical and problem-solving abilities
  • Excellent communication and collaboration skills
Good to have:
  • Knowledge of GWT, MySQL, Oracle, Tomcat, Linux, AWS

Job Details

This is a remote position.

Junior Application Engineer  - Remote Job, 1+ Year Experience


Annual Income: $61K - $75K


A valid work permit is necessary in the US


About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.



Position Summary:

As an experienced application engineer, you will be confident working in Life Sciences to deliver our solution to the delight of customers successfully. Deep knowledge of LIMS, ELN, and SDMS products and their application within the Laboratory setting is essential for success in becoming an expert in the configuration and deployment of products.

Essential Responsibilities:

  • Work with the team to develop and deploy solutions for the customer.

  • Work closely with the customer to understand the business requirements and processes.

  • Configure the Sapio products to meet the time, budget, quality, and customer, success criteria.

  • Train customers on the configuration and use of the products

  • Support customers in the subsequent implementation of the configuration

  • Follow agile deployment methodology.

  • Document customer feedback and ensure issues are addressed to provide the best customer experience and ultimate success of the project.

Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Education/Experience:

  • A Degree or equivalent in Computer Science

  • 1+ years of Life Sciences experience working within a Lab (preferably introducing new IT solutions)

  • 1+ years of experience with configuring either LIMS ELN or similar software.

  • Preferred: knowledge of one or more of GWT, MySQL, Oracle, Tomcat, Linux, AWS

Required Skills & Abilities:

  • Strong programming skills with detailed knowledge of Java

  • Strong analytical, problem-solving, and fact-finding skills.

  • Self-starter who is happy to learn from colleagues.

  • Highly respected and trusted by the customers you work with

  • Problem solver

  • Great communicator

  • Determined and persistent.


Why Patterned Learning LLC?


Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.


The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.



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