Responsibilities:
- Help build model monitoring systems across model types like regression, classification with structured & unstructured datasets.
- Build high-performance multi-tenant deployment architecture that works across frameworks like PyTorch, sklearn, TensorFlow.
- Help realize the product vision: Production-ready machine learning models with monitoring within moments, not months.
- Help companies deploy their machine learning models at scale across a wide range of use-cases and sectors.
- Write maintainable, scalable performant python code, Build high volume and high availability analytics systems, Push the state of the art of MLOPs to push the industry ahead.
Requirements:
- 3+ years work experience with production-grade python- preferably contribution to open source repost.
- Prior experience with ML monitoring, observability & explainability systems, and familiarity with tools for data science like Pandas, Notebooks, Numpy, Scipy, etc.
- Comfortable working in a Linux environment, experience with one relational & 1 non-relational DB is preferred.
- Some working experience with TensorFlow or PyTorch is preferred.
- Experience with model analysis and experimentation frameworks like MLFlow, W& B;, tfma is preferred.
About Building Pivotal DS
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About UpSolve
Work on cutting-edge tech stack. Build innovative solutions. Computer Vision, NLP, Video Analytics and IOT.
Job Role
- Ideate use cases to include recent tech releases.
- Discuss business plans and assist teams in aligning with dynamic KPIs.
- Design solution architecture from input to infrastructure and services used to data store.
Job Requirements
- Working knowledge about Azure Cognitive Services.
- Project Experience in building AI solutions like Chatbots, sentiment analysis, Image Classification, etc.
- Quick Learner and Problem Solver.
Job Qualifications
- Work Experience: 2 years +
- Education: Computer Science/IT Engineer
- Location: Mumbai
Job Description:
1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
b. Improve Model accuracy to deliver greater business impact
c.Estimate business impact due to deployment of model
2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines
4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch
5.Experience in using Deep learning models with text, speech, image and video data
a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
c.Knowledge of State of the art Deep learning algorithms
6.Optimize and tune Deep Learnings model for best possible accuracy
7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau
8.Work with application teams, in deploying models on cloud as a service or on-prem
a.Deployment of models in Test / Control framework for tracking
b.Build CI/CD pipelines for ML model deployment
9.Integrating AI&ML models with other applications using REST APIs and other connector technologies
10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.
· Technology/Subject Matter Expertise
- Sufficient expertise in machine learning, mathematical and statistical sciences
- Use of versioning & Collaborative tools like Git / Github
- Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
- Develop prototype level ideas into a solution that can scale to industrial grade strength
- Ability to quantify & estimate the impact of ML models.
· Softskills Profile
- Curiosity to think in fresh and unique ways with the intent of breaking new ground.
- Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
- Ability to think ahead, and anticipate the needs for solving the problem will be important
· Ability to communicate key messages effectively, and articulate strong opinions in large forums
· Desirable Experience:
- Keen contributor to open source communities, and communities like Kaggle
- Ability to process Huge amount of Data using Pyspark/Hadoop
- Development & Application of Reinforcement Learning
- Knowledge of Optimization/Genetic Algorithms
- Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
- Optimize and tune deep learning model for best possible accuracy
- Understanding of stream data processing, RPA, edge computing, AR/VR etc
- Appreciation of digital ethics, data privacy will be important
- Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
- Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
Job Description
Data scientist with strong background in data mining, machine learning, recommendation systems, and statistics. Should possess signature strengths of a qualified mathematician with ability to apply concepts of Mathematics, Applied Statistics, with specialization in one or more of NLP, Computer Vision, Speech, Data mining to develop models that provide effective solution.. A strong data engineering background with hands-on coding capabilities is needed to own and deliver outcomes.
A Master’s or PhD Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience, 7+ years of industry experience in predictive modelling, data science and analysis, with prior experience in a ML or data scientist role and a track record of building ML or DL models.
Responsibilities and skills:
● Work with our customers to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
● Selecting features, building and optimizing classifiers using ML techniques ● Data mining using state-of-the-art methods, create text mining pipelines to clean & process large unstructured datasets to reveal high quality information and hidden insights using machine learning techniques
● Should be able to appreciate and work on Computer Vision problems – for example extract rich information from images to categorize and process visual data— Develop machine learning algorithms for object and image classification, Experience in using DBScan, PCA, Random Forests and Multinomial Logistic Regression to select the best features to classify objects.
OR
● Deep understanding of NLP such as fundamentals of information retrieval, deep learning approaches, transformers, attention models, text summarisation, attribute extraction, etc. Preferable experience in one or more of the following areas: recommender systems, moderation of user generated content, sentiment analysis, etc.
OR
● Speech recognition, speech to text and vice versa, understanding NLP and IR, text summarisation, statistical and deep learning approaches to text processing. Experience of having worked in these areas.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Needs to appreciate deep learning frameworks like MXNet, Caffe 2, Keras, Tensorflow
● Experience in working with GPUs to develop models, handling terabyte size datasets ● Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, mlr, mllib, Scikit-learn, caret etc - excellence in at least one of these is highly desirable ● Should be able to work hands-on in Python, R etc. Should closely collaborate & work with engineering teams to iteratively analyse data using Scala, Spark, Hadoop, Kafka, Storm etc.,
● Experience with NoSQL databases and familiarity with data visualization tools will be of great advantage
Responsibilities include:
- Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
- Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
- Build data ingestion and data transformation infrastructure
- Automate infrastructure that the data science team uses
- Perform statistical analysis and tune the results so that the organization can make better-informed decisions
- Set up and manage AI development and product infrastructure
- Be a good team player, as coordinating with others is a must
- Demonstrate ability in NLP/ML/DL project solutions and architectures.
- Strong ability in developing NLP tool and end to end solutions.
- Minimum 1 year of experience in text cleaning, data wrangling, and text mining.
- Good understanding of Rule-based, statistical, and probabilistic NLP techniques.
- Collaborate with analytics team members to design, implement, and develop enterprise-level NLP capabilities, including data engineering, technology platforms, and algorithms.
- Good knowledge of NLP approaches and concepts like topic modelling, text summarization, semantic modelling, Named Entity recognition, etc.
- Evaluate and benchmark the performance of different NLP systems and provide guidance on metrics and best practices.
- Test and deploy promising solutions quickly, managing deadlines and deliverables while applying latest research and techniques.
- Collaborate with business stakeholders to effectively integrate and communicate analysis findings across NLP solutions.
Key Technical Skills:
- Hands on experience in building NLP models using different NLP libraries and toolkit like NLTK, Stanford NLP, TextBlob, OCR etc.
- Strong programming skills in Python
- Good to have programming skill: Java/Scala/C/C++.
- Strong problem solving, logical and communication skills.
Tags: Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Toolkit (NLTK), Analytics
THE IDEAL CANDIDATE WILL
- Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
- Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
- Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
- Work hands-on across various MLOps problems and provide thought leadership
- Grow and manage large teams with diverse skillsets
- Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists
ELIGIBILITY CRITERIA
- BE/BTech/MTech (Specialization/courses in ML/DS)
- At-least 7+ years of Consulting services delivery experience
- Very strong problem-solving skills & work ethics
- Possesses strong analytical/logical thinking, storyboarding and executive communication skills
- 5+ years of experience in Python/R, SQL
- 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
- Hands on work experience in DevOps
- Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
- Exposure on cloud technologies like Azure, AWS or GCP
- Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
- Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
- Experience with one or more Container-ecosystem (Docker, Kubernetes)
- Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
- Good understanding of OOP & Data Structures concepts
Nice to Have:
- Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
- Experience in Helm is a plus
- Strong understanding of data infrastructure, data warehouse, or data engineering
You can expect to –
- Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
- Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
- Work in a diverse environment that keeps evolving
- Hone your entrepreneurial skills as you contribute to growth of the organization
Duties and Responsibilities:
Research and Develop Innovative Use Cases, Solutions and Quantitative Models
Quantitative Models in Video and Image Recognition and Signal Processing for cloudbloom’s
cross-industry business (e.g., Retail, Energy, Industry, Mobility, Smart Life and
Entertainment).
Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types
Provide R&D support to productize research prototypes.
Explore emerging tools, techniques, and technologies, and work with academia for cutting-
edge solutions.
Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
Team Management Skills
Academic Qualification
7+ years of professional hands-on work experience in data science, statistical modelling, data
engineering, and predictive analytics assignments
Mandatory Requirements: Bachelor’s degree with STEM background (Science, Technology,
Engineering and Management) with strong quantitative flavour
Innovative and creative in data analysis, problem solving and presentation of solutions.
Ability to establish effective cross-functional partnerships and relationships at all levels in a
highly collaborative environment
Strong experience in handling multi-national client engagements
Good verbal, writing & presentation skills
Core Expertise
Excellent understanding of basics in mathematics and statistics (such as differential
equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen
vectors, Markov models, Fourier analysis).
Building data analytics models using Python, ML libraries, Jupyter/Anaconda and Knowledge
database query languages like SQL
Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM,
Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the
fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis
of a lot of predictive performance or algorithm optimization techniques.
Deep learning : CNN, neural Network, RNN, tensorflow, pytorch, computervision,
Large-scale data extraction/mining, data cleansing, diagnostics, preparation for Modeling
Good applied statistical skills, including knowledge of statistical tests, distributions,
regression, maximum likelihood estimators, Multivariate techniques & predictive modeling
cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis
Experience with Data Visualization Tools like Tableau, Power BI, Qlik Sense that help to
visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical
and non-technical audience
Capability for continuous learning and knowledge acquisition.
Mentor colleagues for growth and success
Strong Software Engineering Background
Hands-on experience with data science tools
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.
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