Technical Architect - MLE

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