Technical Architect - MLE

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!

Work location: Hybrid (Mumbai/Bangalore/Trivandrum)
Experience in Years: Overall 10-20 Years in which 7+ is into designing, developing, & deploying AI/ML

Role & 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 associate architects, engineers and young talent within the organization, define and track their
growth parameters.

Must have skills:
● Strong interpersonal and written skills with clear and precise communication.
● 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.
● 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.
● 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 (Textract,Vision, Text Extraction, Speech-to-text,
Text-to-speech, Translation etc.).
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
● Cloud Certification - Machine Learning and/or Cloud Architect