Machine learning Architect-AI Agent / CCAI

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.

challenging development and data integration problems related to ML

Model training and deployment in Enterprise Applications.

that may affect the Data Science / ML life-cycle management in enterprise

application portfolio.

domains.

with the stakeholders and various IT teams within the company to facilitate

the design and development of ML / AI solutions.

to schedule, quality, and customer satisfaction.

different AI / ML use cases.

implementations.

ensure excellence in delivery to customers.

practices within the organization, and ensure adherence to those.

and track their growth parameters.

Responsibilities :

communication.

with clients.

business problems across domains.

Scikit-Learn, Pandas, Matplotlib, Seaborn, D3.js,Tensorflow, Pytorch, Keras.

(Decision-trees, Random Forests, SVM, ANNs), Clustering(k-means, DBSCAN),

Dimension Reduction (PCA, SVD), Ensemble techniques (XGBoost, CatBoost,

LightGBM).

blurring, histogram equalization, etc using OpenCV.

YOLO, SSD, Detectron2 for various use cases related toimage such as Image

Classification, Object Detection, Image Segmentation, etc.

Tokenization, POS tagging, Coreference Resolution,Dependency and

Constituency Parsing, Named Entity Recognition.

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

using algorithms like Linear Regression, Neural Networks, Exponential

Smoothing, Holt’s Winters, ARIMA, SARIMA, LSTM.

performance metrics based on the use case and should be able to perform

cross-validation, hyperparameter tuning, and error analysis.

using open source or cloud tools such as MLflow, Kubeflow, TFX, Feature

Store, etc.

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 :

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.

What’s in it for you?

1. The experience of working in a category defining high growth startups in the

transformational AI, Decision Science and Big Data Domain.

2. The opportunity of getting on boarded to the phenomenal growth journey

and helping the customers take the next big leap in digital transformation

3. 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.

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

balance.