Architect - Machine Learning

Must have skills:

● Strong interpersonal and written skills with clear and precise communication

● Experience working in an Agile and competitive environment

● Stakeholder interaction experience both within the organization and outside with clients

● Strong analytical and quantitative skill set with proven experience solving business problems across domains

● Very good with EDA, Hypothesis Testing, Feature Engineering

● Hands-on with Python/R programming and ML/Viz. libraries/frameworks like Scikit-Learn, Pandas, Matplotlib, Seaborn, D3.js, Tensorflow, Pytorch, Keras.

● Experience with ML algorithms such as Regression and Classification (Decision-trees, Random Forests, SVM, ANNs), Clustering (k-means, DBSCAN), Dimension Reduction (PCA, SVD), Ensemble techniques (XGBoost, CatBoost, LightGBM)

● Basic image enhancement techniques such contrast enhancement, blurring, histogram equalization, etc using OpenCV

● Experience with DL/CV techniques like CNNs, Faster RCNN, Mask RCNN, YOLO, SSD, Detectron2 for various use cases related to image such as Image Classification, Object Detection, Image Segmentation, etc

● Traditional NLP - Bag of words, tf-idf, Stemming, Lemmatization, Tokenization, POS tagging, Coreference Resolution, Dependency and Constituency Parsing, Named Entity Recognition

● NLP: NLU vs NLG, Vector Space modeling and text representation techniques in NLP, Knowledge/experience using RNNs, LSTMS, Sequence modeling and Attention mechanism, Transformers, BERT, GPT and their SOTA variants, Sequence modeling, Attention modeling, BERT, Transformers.Using the above-mentioned techniques for Text classification, Sentiment Analysis,

Semantic similarity, Entity Extraction, Document summarization, NLI, Question-Answering, Machine Translation, etc

● Forecasting modeling experience both on univariate and multivariate data using algorithms like Linear Regression, Neural Networks, Exponential Smoothing, Holt’s Winters, ARIMA, SARIMA, LSTM

● Identify appropriate objective functions, regularization techniques, performance metrics based on the use case and should be able to perform cross-validation, hyperparameter tuning, and error analysis

Nice to have skills:

● Any pre-sales experience

● Hands-on experience with any visualization tool like Tableau, Power BI, Looker Studio

● Build APIs using frameworks such as Flask, Django, FastAPI

● Hands-on AI/ML experience with any one cloud platform (GCP, Azure, AWS) either using the modeling options (Vertex

AI, SageMaker, Azure ML) or leveraging ML APIs (Speech-to-text, Text-to-speech, Translation, Vision, Text Extraction, Language)

● Distributed training for deep learning using frameworks like PyTorch, TensorFlow

● Advanced image processing using OpenCV, Feature Detection and Matching using SIRF/SURF/FAST/BRIEF

● Advanced recommender systems using model based techniques like KNN, Matrix Factorization, SVD, etc and and/or Deep Learning methods

● Docker containerization of microservices, deployment on cloud compute resources and orchestration using popular frameworks like Kubernetes

● Experience building and deploying AI/ML solutions in production using open source or cloud tools such as MLflow, Kubeflow, TFX, Feature Store, etc

● Experience with either or all of Knowledge Graphs, Federated Learning, Deep Reinforcement Learning

● Experience/Knowledge working on Intelligent Document processing solutions using open-source technologies like OCR using Tesseract, text-block, ROI detection using OpenCV, etc.

● Experience/Knowledge working on solutions using Cloud based Document processing products like Google Document AI, Amazon Textract, Microsoft Azure Form Recognizer, etc.

● Cloud Certification - Machine Learning and/or Cloud Architect

Roles & Responsibilities:

● Ability to multitask and work on multiple engagements related to different domains

● Work in a highly collaborative and fast paced environment by interacting with the stakeholders and various IT teams within the company to facilitate the design and development of ML/AI solutions

● Responsible for the successful delivery of all allocated projects with respect to schedule, quality, and customer satisfaction

● Work with the pre-sales team on RFP, RFIs and help them solutioning for different AI/ML use cases

● Evaluate latest technologies, decide technical feasibility, and drive solution implementations

● Follow Agile standards and methodologies in all phases of the project and ensure excellence in delivery to customers

● Refine coding standards, software development guidelines, and best practices within the organization, and ensure adherence to those

● Mentor juniors within the organization, define and track their growth parameters