Tech Architect - ML

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Designation: Architect - Machine Learning
Experience in Years: 10 - 14 yrs
Work location: Bangalore/Mumbai (Hybrid)

Must have skills:

• Strong interpersonal and written skills with clear and precise communication
• Design and own the Alibaba Cloud platform architecture aligned to an existing Azure-based reference architecture.
• Translate Azure PaaS, Kubernetes, IoT, data, and observability services into Alibaba Cloud equivalents with minimal application change.
• Define a cloud-agnostic, portable platform blueprint supporting deployments across Azure, GCP, and Alibaba Cloud.
• Experience working in an Agile and competitive environment
• Technical leadership experience handling large teams
• 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
• Proven experience building and deploying AI/ML solutions in production using open source or cloud tools such as MLflow, Kubeflow, TFX, Feature Store, etc
• 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 the APIs (Speech-to-text, Text-to-speech, Translation, Vision, Text Extraction)

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
• 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 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, Alibaba Cloud

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 other architects and young talent within the organization, define and track their growth parameters