Lead AI/ML Architect

Excellent Opportunity with Global MNC :

Masters degree in AI/ML with 5+ years hands-on experience in DS, AI, ML, DL, NLP, RL; expertise in Python, R, TensorFlow, PyTorch, AWS/GCP platforms.

Lead AI/ML strategy, build CoE and teams, develop and deploy machine learning models for Electronic Warfare and SIGINT domains, manage large-scale AI projects, and collaborate with domain experts.

Experience Requirements:

• Good 5+ years of relevant hands on experience in AI/ML Architecture, Machine Learning Solutions, Customer-Facing AI Applications, Conversational AI, Predictive Analytics, Operational Intelligence, Data Science, MLOps, NVIDIA Deep Learning, AWS Machine Learning, Microsoft Azure AI/ML, Google Cloud AI/ML, CAIP.

• Experience working in range of problems involving various areas of AI ML.

• Hands on experience developing models using ML, DL, ADL, NLP and RL strategy.

• Leading innovation effort.

• Experience in Python, R, AI Framework, TensorFlow, PyTorch.

• Experience building AI ML pipeline.

• Experience handling large dataset, quantitative and statistical analysis.

• Good knowledge of statistics.

• Implementation knowledge of various algorithms, optimizers.

• Experience with Natural Language models and approaches including Topic Modeling, Text Classification, Entity Extraction, Neural Language (CNN, BiDirectional LSTM, Elmo, Bert).

• Deep understanding of text representation techniques (n-grams, bag of words, tf-idf, word embeddings, sense embeddings) and frameworks (glove, word2vec).

• Experience managing large scale AI ML projects using AWS / Google platform.

• Auto ML.

• Publication.

• Experience in AI frameworks, such as PyTorch, TensorFlow.

Responsibilities:

• Apply machine learning models, tools, and techniques to the Electronic Warfare and SIGINT domains.

• Assist with algorithm and model integration with hardware and software components.

• Assist with the collection, generation, and augmentation of data sets.

• Perform verification and validation of system functionality and performance.

• Work with domain subject matter experts to identify algorithm and model requirements.

• Stay updated on state-of-the-art ML techniques and technologies.

• Experience with some of: Temporal Data Streams, Digital Signal Processing, Wireless Communications, Intelligent Agents, Artificial Intelligence (AI), Deep Reinforcement Learning, Neural Networks, Python, Matlab, Tensorflow, Keras, Kubeflow, Sagemaker.