AI / ML Engineer - Data Science

Lightning Job By Cutshort ⚡

As part of this feature, you can expect status updates about your application and replies within 72 hours (once the screening questions are answered)

About Crosscope Inc.

Founded by a team of Stanford University and GE Healthcare researchers, Crosscope is a medical AI software company developing cutting-edge deep learning technology for pathologists to speed up diagnosis and deliver data-driven insights through imaging biomarkers in rendering a more accurate and reliable cancer diagnosis.

We here at Crosscope recognize that the key to success lies in valuing the minds, experiences and perspectives of people from all walks of life. Crosscopeis proud to value diversity and be an equal employment opportunity employer.

We offer employees challenging work experiences, collaborative team

environments, and comprehensive benefits. However, the strongest reason to work at Crosscope is the opportunity to bring a true difference in peoples’ lives by providing reliable cancer diagnosis.

Key Responsibilities:

• Design and develop predictive models, ML algorithms, statistical analyses and feature engineering to solve complex problems for hardware feedback, ease of use for customers, retrospective data analysis and expanding product capabilities
• Evaluate the performance of AI/ML/Computer Vision models/algorithms using relevant metrics, ensuring they meet industry-specific requirements.
• Participate in the full lifecycle of AI projects, from ideation and model development to implementation, validation, and deployment.
• Create informative and visually appealing data visualizations and reports.
• Identify opportunities for innovation and improvement in analytics and data-driven decision-making.
• Communicate complex computer vision concepts, and project outcomes to a diverse audience, including technical and non-technical stakeholders.
• Provide mentorship and guidance to junior AI scientists and data scientists

Qualifications and Skills:

• Seeking candidates with a Ph.D. in computer vision, machine learning, computer science, clinical machine learning, or a related field, or equivalent practical experience (e.g., a Master's degree plus 6 years of relevant industry experience)
• Proven 6 years of professional experience as a Data Scientist with a significant focus on healthcare data analysis and modeling.
• Proven expertise in developing models for diverse computer vision tasks, including segmentation, recognition, classification, and domain adaptation.
• Exceptional programming skills in Python, with the ability to process TB-scale image datasets using Linux/Bash.
• Proficiency in utilizing modern deep learning frameworks such as PyTorch, JAX, Keras, etc.
• Extensive hands-on experience in working with biomedical imaging modalities.
• Strong familiarity with modern representation learning approaches like self-supervised learning, transfer learning, multi-modal modeling, few-shot learning, and more.
• Excellent communication skills, with the ability to communicate technical concepts to non-technical healthcare stakeholders.
• Passion for creating a positive impact on the world.

• experience in algorithm development with a focus on signal processing, pattern recognition, machine learning, classification, data mining, and other areas of machine intelligence.
• Ability to analyse data streams from multiple sensors and develop algorithms to extract accurate and meaningful sport metrics.
• Should have a deeper understanding of IMU sensors and Biosensors like HRM, ECG
• A good understanding on Power and memory management on embedded platform

•  Expertise in the design of multitasking, event-driven, real-time firmware using C and understanding of RTOS concepts
• Knowledge of Machine learning, Analytical and methodical approaches to data analysis and verification and Python
• Prior experience on fitness algorithm development using IMU sensor
•  Interest in fitness activities and knowledge of human body anatomy

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
4. Work with Data, Analytics & Tech team to extract, arrange and analyze data
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
7. Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
8. Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
9. Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.

1. SQL
2. Ruby or Python(Ruby preferred)
3. Apache-Hadoop based analytics
4. Data warehousing
5. Data architecture
6. Schema design
7. ML

1.  Prior experience of 2 to 5 years as a Data Engineer.
2. Ability in managing and communicating data warehouse plans to internal teams.
3. Experience designing, building, and maintaining data processing systems.
4. Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
5. Excellent analytic skills associated with working on unstructured datasets.
6. Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.

Who Are We

A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.

ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.

WHY US

• Join top AI company
• Grow with your best companions
• Continuous pursuit of excellence, equality, respect
• Competitive compensation and benefits

You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.

To learn more about how we work, please check out

https://www.orbo.ai/.

Description:

We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.

Responsibilities:

• Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
• Lead a team of ML engineers in developing an industrial AI product from scratch
• Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
• Tune the models to achieve high accuracy rates and minimum latency
• Deploying developed computer vision models on edge devices after optimization to meet customer requirements

Requirements:

• Bachelor’s degree
• Understanding about depth and breadth of computer vision and deep learning algorithms.
• 4+ years of industrial experience in computer vision and/or deep learning
• Experience in taking an AI product from scratch to commercial deployment.
• Experience in Image enhancement, object detection, image segmentation, image classification algorithms
• Experience in deployment with OpenVINO, ONNXruntime and TensorRT
• Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
• Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
• Proficient understanding of code versioning tools, such as Git

Our perfect candidate is someone that:

• is proactive and an independent problem solver
• is a constant learner. We are a fast growing start-up. We want you to grow with us!
• is a team player and good communicator

What We Offer:

• You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
• You will be in charge of what you build and be an integral part of the product development process
• Technical and financial growth!

• Does analytics to extract insights from raw historical data of the organization. 
• Generates usable training dataset for any/all MV projects with the help of Annotators, if needed.
• Analyses user trends, and identifies their biggest bottlenecks in Hammoq Workflow.
• Tests the short/long term impact of productized MV models on those trends.
• Skills - Numpy, Pandas, SPARK, APACHE SPARK, PYSPARK, ETL mandatory. 

About us

Skit (previously known as http://vernacular.ai/" target="_blank">Vernacular.ai) is an AI-first SaaS voice automation company. Its suite of speech and language solutions enable enterprises to automate their contact centre operations. With over 10 million hours of training data, its product - Vernacular Intelligent Voice Assistant (VIVA) can currently respond in 16+ languages, covering over 160+ dialects and replicating human-like conversations.

Skit currently serves a variety of enterprise clients across diverse sectors such as BFSI, F&B, Hospitality, Consumer Electronics and Travel & Tourism, including prominent clients like Axis Bank, Hathway, Porter and Barbeque Nation. It has been featured as one of the top-notch start-ups in the Cisco Launchpad’s Cohort 6 and is a part of the World Economic Forum’s Global Innovators Community. It has has also been listed in Forbes 30 Under 30 Asia start-ups 2021 for its remarkable industry innovation.

We are looking for ML Research Engineers to work on the following problems:

• Spoken Language Understanding and Dialog Management.
• Language semantics, parsing, and modeling across multiple languages.
• Speech Recognition, Speech Analytics and Voice Processing across multiple languages.
• Response Generation and Speech Synthesis.
• Active Learning, Monitoring and Observability mechanisms for deployments.

Responsibilities

• Design, build and evaluate Machine Learning solutions.
• Perform experiments and statistical analyses to draw conclusions and take modeling decisions.
• Study, implement and extend state of the art systems.
• Take part in regular research reviews and discussions.
• Build, maintain and extend our open source solutions in the domain.
• Write well-crafted programs at all levels of the system. This includes the data pipelines, experiment prototypes, fast and scalable deployment models, and evaluation, visualization and monitoring systems.

Requirements

• Practical Machine Learning experience as demonstrated by earlier works.
• Knowledge of and ability to use tools from theoretical and practical aspects of computer science. This includes, but is not limited to, probability, statistics, learning theory, algorithms, software architecture, programming languages, etc.
• Good programming skills and ability to work with programs at all levels of a finished Machine Learning product. We prefer language agnosticism since that exemplifies this point.
• Git portfolios and blogs are helpful as they let us better evaluate your work.

• What information we collect during our application and recruitment process and why we collect it;
• How we use that information; and
• How to access and update that information.

• Your name, address, email address, telephone number and other contact information;
• Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
• Information from interviews and phone-screenings you may have, if any;
• Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
• Details of how you heard about the position you are applying for;
• Reference information and/or information received from background checks (where applicable), including information provided by third parties;
• Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
• Information related to any assessment you may take as part of the interview screening process.

• Assessing your skills, qualifications and interests against our career opportunities;
• Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
• Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
• Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
• Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
• Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.