Machine Learning Architect

Job Summary :

Role : Sr.Technical Lead Applied AI.

Experience : 11 Years.

We are seeking a highly experienced ML & Applied AI Architect with a specialization in deep learning and generative models to join our dynamic team.

In this senior role, you will evangelize the latest AI research and guide the strategic architectural direction of our AI modeling and implementation efforts, including the evaluation and fine-tuning of large language models (LLMs), and the evolving automation based on customer needs.

- The ideal candidate has a robust understanding of the recent developments in reinforcement learning with human feedback (RLHF) and can adeptly apply this knowledge in a practical setting.

- They will be a self-motivated, entrepreneurial, and demonstrated team-player, as well as an early thought leader and hands-on implementer along with the teams and developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.

- Defining, designing and delivering ML architecture patterns operable in native and hybrid cloud architectures.

- Research, analyze, recommend and select technical approaches to address challenging development and data integration problems related to ML.

- Model training and deployment in Enterprise Applications.

- Perform research activities to identify emerging technologies and trends that may affect the Data Science/ ML life-cycle management in enterprise application portfolio.

- 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.

Responsibilities :

- 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, ,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 toimage 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.

What is Required :

- Forecasting modeling experience both on univariate and multivariate data using algorithms like Linear Regression, Neural Networks, Exponential Smoothing, Holts 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 (VertexAI, SageMaker, Azure ML) or leveraging the APIs (Speech-to-text, Text-to-speech, Translation, Vision, Text Extraction).

Nice to have skills :

- In-depth experience in AI/ML and Data analytics services offered.

- Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.

Whats in it for you ?

- The experience of working in a category defining high growth startups in the transformational AI, Decision Science and Big Data Domain.

- The opportunity of getting on boarded to the phenomenal growth journey and helping the customers take the next big leap in digital transformation.

- The opportunity to work with a diverse, lively and proactive group of techies who are constantly raising the bar on the art of translating mounds of data into tangible business value for clients.

- Flexible working options available to foster productivity and work/life balance.