Introduction
Synapsica is a series-A funded HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don't have to rely on cryptic 2 liners given to them as a diagnosis.
Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting. We are backed by IvyCap, Endia Partners, YCombinator and other investors from India, US, and Japan. We are proud to have GE and The Spinal Kinetics as our partners. Here’s a small sample of what we’re building: https://www.youtube.com/watch?v=FR6a94Tqqls
Your Roles and Responsibilities
The Integration Software Manager is responsible for building products which integrate Synapsica AI based radiology software products with client side systems and horizontal app deployment platforms. The Integration Software Manager works with clients, product managers, internal software team and business development team to design and build products which allow Synapsica apps to integrate with external systems. The Integration Software Manager works with a team of engineers to build these products and owns the end-to-end delivery. The role requires understanding of various technologies and ability to quickly learn and execute development plans with new technologies. At Synapsica, we have used Javascript, React, Nodejs, Mongodb, Python, Dicom, HL7, AWS suite technologies to name a few.
This is a highly visible role working directly with founders and requires a mix of technical acumen and team leadership skills to drive the execution of the platform. This person must be creative, ask questions, and be comfortable challenging the status quo. The position is based in our Bangalore office.
Primary Responsibilities
- Work at a key intersection between customers, AI team, product engineering teams, and business development teams
- Partner cross-functionally with product managers, core platform engineers, and AI team to improve adoption of our applications
- Build modules that help onboard new customers onto our radiology platform
- Own end-to-end designing, documentation, development and delivery of softwares that enable clients to use our radiology products effectively
- Ensure analysis, efficiency, responsiveness, scalability and cross-platform compatibility of applications through captured metrics, testing frameworks, and debugging methodologies.
- Technical documentation through all stages of development
- Create design, develop modules, and coordinate efforts with the development team, working on application architectural implementation
- Collaborate with Product Analysts and Product Managers to estimate and plan work and provide status updates to stakeholders
- Create a close working relationship with business partners to identify the pain points and provide better experience to clients
- Establish strong relationships, and proactively communicate, with team members as well as individuals across the organisation
Requirements
- Degree in Computer Science or related discipline with 6-10 years of experience.
- Proficiency with server side languages such as Nodejs, Python, shell scripting
- Quick adoption of new technologies .
- Proficiency with at least one no-sql database such as MongoDB.
- Experience with platform components and REST APIs, to define platform interfaces and boundaries
- Experience creating a loosely coupled, services oriented design that can scale for large volumes of data
- Experience supporting extensibility, to plug new modules or services without requiring re-design
- Expertise in object oriented programming and applying OO principles patterns
- Good command over CI/CD processes.
- Excellent communication and collaboration skills with project members and stakeholders.
- Good problem solving skills.
- Very high sense of ownership.
- Deep interest and passion for technology
- Prior experience of leading software teams
- Ability to plan projects, execute them and meet the deadline
About Synapsica Healthcare
At Synapsica, we are creating AI-first PACS and radiology workflow solution that is fast, secure and automates reporting tasks, helping radiologists create high quality reports quicker.
Our goal is to enable radiologists with fast, easy to use AI technology that helps generate high quality, evidence-based reports to significantly improve patient care.
Synapsica is a growth stage HealthTech startup founded by alumni from AIIMS, IIT-KGP & IIM-A with a vision to increase the accessibility of diagnostic services globally. We are solving the problem of shortage of radiologists by bringing in automation at various stages of the radiology reporting process to reduce reporting time, costs & error rates & deliver efficiencies for better patient care.
We are deploying Computer Vision based Neural Networks models to identify biomarkers of pathologies in Radiology scans. These models not just identify pathologies, but provide detailed characterization of what exactly constitutes that pathology.
RADIOLens is an intuitive, AI enabled, cloud based RIS/PACS solution that makes diagnostic radiology workflows smoother. It provides Faster image uploading with Zero loss in image quality. RADIOLens helps automate mundane reporting tasks so radiologists can focus on clinical correlations for their patients.
Spindle for MRI Spine helps with reporting of age related degeneration of spine. It automatically identifies key spinal mensurations and provides a detailed, standardized report with annotated images of abnormal various spinal elements. It quickly identifies variations and pathologies, such as spinal deformations, degeneration, identification of listhesis, etc.
SpindleX for stress X-Rays of spine takes automation a step further by generating a one click automated reporting for all XR cases. These reports quantify all abnormalities and features of injury or early degeneration such as spinal instability, abnormal intersegmental motion etc. Illustrative graphs and tables comparing extent of injury against standards are automatically included in the report making it easier to generate qualitative reports with visual evidence.
Crescent segregates normal, abnormal and bad quality captures in chest X-rays. It identifies bad quality scans that need re-capture and for good scans it localizes and characterizes common lesions & abnormalities. With Crescent, standard, pre-filled reports are generated for normal radiographs and critical studies are prioritized in the worklist.
We are backed by Y Combinator and other investors from India, US and Japan. We are proud to have GE, AIIMS, the Spinal Kinetics as our partners.
Here’s a small sample of what we’re building: https://youtu.be/MtWSF-x2sxY
Join us, if you find this as exciting as we do!
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