The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc. ) and traditional Image Processing (OpenCV etc. ). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- 2 - 4 years of relevant experience in solving complex real-world problems at scale via deep learning, computer vision or AI
- Python, cuDNN, Tensorflow/PyTorch/Keras (or similar Deep Learning frameworks).
- CNNs, RNNs, Transfer learning (for image classification, segmentation, object detection etc).
- Image Processing techniques using OpenCV or other white-box image feature extraction algorithms.
- End to end deployment of deep learning models.
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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Introduction
Synapsica is a growth stage 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 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 YCombinator and other investors from India, US and Japan. We are proud to have GE, AIIMS, and the Spinal Kinetics as our partners.
Your Roles and Responsibilities
The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc.) and traditional Image Processing (OpenCV etc.). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- Strong problem-solving ability
- Prior experience with Python, cuDNN, Tensorflow, PyTorch, Keras, Caffe (or similar Deep Learning frameworks).
- Extensive understanding of computer vision/image processing applications like object classification, segmentation, object detection etc
- Ability to write custom Convolutional Neural Network Architecture in Pytorch (or similar)
- Experience of GPU/DSP/other Multi-core architecture programming
- Effective communication with other project members and project stakeholders
- Detail-oriented, eager to learn, acquire new skills
- Prior Project Management and Team Leadership experience
- Ability to plan work and meet deadlines
- End to end deployment of deep learning models.
- 3+ years experience in practical implementation and deployment of ML based systems preferred.
- BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
- Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
- Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
- Experience in working on modeling graph structures related to spatiotemporal systems
- Programming skills in Python
- Experience in developing and deploying on cloud (AWS or Google or Azure)
- Good verbal and written communication skills
- Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow
- Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
- Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”.
- Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with data scientists to understand and implement machine learning algorithms.
- Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models.
- Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
- Mentor junior team members
Who we have in mind:
- Graduate in Computer Science or related field, or equivalent practical experience.
- 4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
- Proficiency with SQL, Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
- Familiarity with deep learning frameworks such as TensorFlow or Keras
- Experience with Computer Vision (OpenCV), NLP frameworks (NLTK, SpaCY, BERT).
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Understand machine learning principles (training, validation, etc.)
- Strong hands-on knowledge of data query and data processing tools (i.e. SQL)
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Experience deploying highly scalable software supporting millions or more users
- Experience building applications on cloud (AWS or Azure)
- Experience working in scrum teams with Agile tools like JIRA
- Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users
Requirements
Basic Qualifications:
- Five+ years experience working in a Big Data Software Development role
- Experience managing and deploying ML models in real world environments
- Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
- Experience working with Python, Scala, Spark or other open-source software with data science libraries
- Experience in advanced math and statistics
- Excellent familiarity with command line linux environment
- Able to understand various data structures and common methods in data transformation
- Experience deploying machine learning models
Consulting Staff Engineer - Machine Learning
at Thinkdeeply
Job Description
Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.
Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.
Experience
10+ Years
Location
Bozeman/Hyderabad
Skills
Required Skills:
Bachelors/Masters or Phd in Computer Science or related industry experience
3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow
7+ Years of industry experience in scripting languages such as Python, R.
7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing
Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc
Some experience in setting up large scale training data pipelines.
Some experience in using Cloud services such as AWS, GCP, Azure
Desired Skills:
Experience in building deep learning models for Computer Vision and Natural Language Processing domains
Experience in productionizing/serving machine learning in industry setting
Understand the principles of developing cloud native applications
Responsibilities
Collect, Organize and Process data pipelines for developing ML models
Research and develop novel prototypes for customers
Train, implement and evaluate shippable machine learning models
Deploy and iterate improvements of ML Models through feedback
Machine Learning Specialist - Deep Learning/NLP
JD : ML/NLP Tech Lead
- We are looking to hire an ML/NLP Tech lead who can own products for a technology perspective and manage a team of up to 10 members. You will play a pivotal role in re-engineering our products, transformation, and scaling of AssessEd
WHAT ARE WE BUILDING :
- A revolutionary way of providing continuous assessments of a child's skill and learning, pointing the way to the child's potential in the future. This as opposed to the traditional one-time, dipstick methodology of a test that hurriedly bundles the child into a slot, that in-turn - declares- the child to be fit for a career in a specific area or a particular set of courses that would perhaps get him somewhere. At the core of our system is a lot of data - both structured and unstructured.
- We have books and questions and web resources and student reports that drive all our machine learning algorithms. Our goal is to not only figure out how a child is coping but to also figure out how to help him by presenting relevant information and questions to him in topics that he is struggling to learn.
Required Skill sets :
- Wisdom to know when to hustle and when to be calm and dig deep. Strong can do mentality, who is joining us to build on a vision, not to do a job.
- A deep hunger to learn, understand, and apply your knowledge to create technology.
- Ability and Experience tackling hard Natural Language Processing problems, to separate wheat from the chaff, knowledge of mathematical tools to succinctly describe the ideas to implement them in code.
- Very Good understanding of Natural Language Processing and Machine Learning with projects to back the same.
- Strong fundamentals in Linear Algebra, Probability and Random Variables, and Algorithms.
- Strong Systems experience in Distributed Systems Pipeline: Hadoop, Spark, etc.
- Good knowledge of at least one prototyping/scripting language: Python, MATLAB/Octave or R.
- Good understanding of Algorithms and Data Structures.
- Strong programming experience in C++/Java/Lisp/Haskell.
- Good written and verbal communication.
Desired Skill sets :
- Passion for well-engineered product and you are - ticked off- when something engineered is off and you want to get your hands dirty and fix it.
- 3+ yrs of research experience in Machine Learning, Deep Learning and NLP
- Top tier peer-reviewed research publication in areas like Algorithms, Computer Vision/Image Processing, Machine Learning or Optimization (CVPR, ICCV, ICML, NIPS, EMNLP, ACL, SODA, FOCS etc)
- Open Source Contribution (include the link to your projects, GitHub etc.)
- Knowledge of functional programming.
- International level participation in ACM ICPC, IOI, TopCoder, etc
- International level participation in Physics or Math Olympiad
- Intellectual curiosity about advanced math topics like Theoretical Computer Science, Abstract Algebra, Topology, Differential Geometry, Category Theory, etc.
What can you expect :
- Opportunity to work on the interesting and hard research problem, to see the real application of state-of-the-art research into practice.
- Opportunity to work on important problems with big social impact: Massive, and direct impact of the work you do on the lives of students.
- An intellectually invigorating, phenomenal work environment, with massive ownership and growth opportunities.
- Learn effective engineering habits required to build/deploy large production-ready ML applications.
- Ability to do quick iterations and deployments.
- We would be excited to see you publish papers (though certain restrictions do apply).
Website : http://Digitalaristotle.ai
Work Location: - Bangalore
NLP Engineer - Artificial Intelligence
at Artivatic.ai
We are looking for applicants with a strong background in Analytics and Data mining (Web, Social and Big data), Machine Learning and Pattern Recognition, Natural Language Processing and Computational Linguistics, Statistical Modelling and Inferencing, Information Retrieval, Large Scale Distributed Systems and Cloud Computing, Econometrics and Quantitative Marketing, Applied Game Theory and Mechanism Design, Operations Research and Optimization, Human Computer Interaction and Information Visualization. Applicants with a background in other quantitative areas are also encouraged to apply.
We are looking for someone who can create and implement AI solutions. If you have built a product like IBM WATSON in the past and not just used WATSON to build applications, this could be the perfect role for you.
All successful candidates are expected to dive deep into problem areas of Zycus’ interest and invent technology solutions to not only advance the current products, but also to generate new product options that can strategically advantage the organization.
Skills:
- Experience in predictive modelling and predictive software development
- Skilled in Java, C++, Perl/Python (or similar scripting language)
- Experience in using R, Matlab, or any other statistical software
- Experience in mentoring junior team members, and guiding them on machine learning and data modelling applications
- Strong communication and data presentation skills
- Classification (svm, decision tree, random forest, neural network)
- Regression (linear, polynomial, logistic, etc)
- Classical Optimization(gradient descent, newton raphson, etc)
- Graph theory (network analytics)
- Heuristic optimisation (genetic algorithm, swarm theory)
- Deep learning (lstm, convolutional nn, recurrent nn)
Must Have:
- Experience: 3-9 years
- The ideal candidate must have proven expertise in Artificial Intelligence (including deep learning algorithms), Machine Learning and/or NLP
- The candidate must also have expertise in programming traditional machine learning algorithms, algorithm design & usage
- Preferred experience with large data sets & distributed computing in Hadoop ecosystem
- Fluency with databases
