o Convert machine learning models into APIs for applications accessibility
o Running machine learning tests and experiments
o Implementing appropriate ML algorithms
o Creating machine learning models and retraining systems
o Study and transform data science prototypes
o Design machine learning systems
o Research and implement appropriate ML algorithms and tools
o Train and retrain systems when necessary
o Test and deploy models
o Use AI to empower the company with novel capabilities
o Designing and developing machine learning and deep learning system
o Outstanding analytical and problem-solving skills
• Alexa
o Excellent in Python programming
o Experience with AWS Lamda
o Experience with Alexa skills
o Alexa skill directives
o Excellent in NodeJS programming
o Experience with GCP - Dialog Flow and Actions on Google
o Using built-in intents and developing custom intents
o API integration and Postman knowledge
Similar jobs
● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypothesis through theoretical and empirical approaches.
● Productize proven or working models into production quality code.
● Collaborate with product management, marketing and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision makers.
● File patents for innovative solutions that add to company's IP portfolio
Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/PhD in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes (only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Expertise in Python programming language and fluency in analytical tools
such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis
● Strong communication and collaboration skills.
Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
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.
2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research
Only a solid grounding in computer engineering, Unix, data structures and algorithms would enable you to meet this challenge. 7+ years of experience architecting, developing, releasing, and maintaining large-scale big data platforms on AWS or GCP Understanding of how Big Data tech and NoSQL stores like MongoDB, HBase/HDFS, ElasticSearch synergize to power applications in analytics, AI and knowledge graphs Understandingof how data processing models, data location patterns, disk IO, network IO, shuffling affect large scale text processing - feature extraction, searching etc Expertise with a variety of data processing systems, including streaming, event, and batch (Spark, Hadoop/MapReduce) 5+ years proficiency in configuring and deploying applications on Linux-based systems 5+ years of experience Spark - especially Pyspark for transforming large non-structured text data, creating highly optimized pipelines Experience with RDBMS, ETL techniques and frameworks (Sqoop, Flume) and big data querying tools (Pig, Hive) Stickler of world class best practices, uncompromising on the quality of engineering, understand standards and reference architectures and deep in Unix philosophy with appreciation of big data design patterns, orthogonal code design and functional computation models |
- Focusing on developing new concepts and user experiences through rapid prototyping and collaboration with the best-in-class research and development team.
- Reading research papers and implementing state-of-the-art techniques for computer vision
- Building and managing datasets.
- Providing Rapid experimentation, analysis, and deployment of machine/deep learning models
- Based on requirements set by the team, helping develop new and rapid prototypes
- Developing end to end products for problems related to agritech and other use cases
- Leading the deep learning team
- MS/ME/PhD in Computer Science, Computer Engineering equivalent Proficient in Python and C++, CUDA a plus
- International conference papers/Patents, Algorithm design, deep learning development, programming (Python, C/C++)
- Knowledge of multiple deep-learning frameworks, such as Caffe, TensorFlow, Theano, Torch/PyTorch
- Problem Solving: Deep learning development
- Vision, perception, control, planning algorithm development
- Track record of excellence in the machine learning / perception / control, including patents, publications to international conferences or journals.
- Communications: Good communication skills
REQUIREMENT:
- Previous experience of working in large scale data engineering
- 4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
- Previous experience of architecting and designing backend for large scale data processing.
- Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
- Hands-on and have the ability to contribute a key portion of data engineering backend.
- Self-inspired and motivated to drive for exceptional results.
- Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
- Familiarity and experience working with different DB technologies and how to scale them.
RESPONSIBILITY:
- End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
- Build data engineering workflow for large scale data processing.
- Discover opportunities in data acquisition.
- Bring industry best practices for data engineering workflow.
- Develop data set processes for data modelling, mining and production.
- Take additional tech responsibilities for driving an initiative to completion
- Recommend ways to improve data reliability, efficiency and quality
- Goes out of their way to reduce complexity.
- Humble and outgoing - engineering cheerleaders.
JD:
Required Skills:
- Intermediate to Expert level hands-on programming using one of programming language- Java or Python or Pyspark or Scala.
- Strong practical knowledge of SQL.
Hands on experience on Spark/SparkSQL - Data Structure and Algorithms
- Hands-on experience as an individual contributor in Design, Development, Testing and Deployment of Big Data technologies based applications
- Experience in Big Data application tools, such as Hadoop, MapReduce, Spark, etc
- Experience on NoSQL Databases like HBase, etc
- Experience with Linux OS environment (Shell script, AWK, SED)
- Intermediate RDBMS skill, able to write SQL query with complex relation on top of big RDMS (100+ table)