i2c Jobs – Sr. NLP (Natural language processing) Engineer (01 Position)

• Research on creating state-of-the-art, scalable, and self-learning systems for our Business KPIs and their sub-components.
• Design, train and tune a variety of Deep Neural Networks / Machine Learning Models.
• Create models from varying levels of Data Quality and Quantity (Imbalanced, Multi-Domain and/or Multi-Class, Unlabeled) – here your ability to creatively apply Domain Knowledge will be important, such as driving existing model implementations from Supervised to Semi-Supervised Learning.
• Help define and drive improvements related to Architectural Designs, Dialogue-Schemas, Data Acquisition, Feature Transformations and Model Evaluations.
• Standardize and Automate Annotation Practices for efficient utilization for the acquired data.
• Formulate general purpose solutions configurable to accommodate custom requirements for different clients.
• Formulate general purpose solutions configurable to accommodate custom requirements for different clients.
• Perform Data and Error Analysis in order to Improve Models and Understand their Shortcomings.
• Lead all NLP-based projects for AI involving NLP Engineers and Data Analysts.
• Communicate and Work effectively with Team Members and Other Teams (on-site and/or remotely).
  

We Are Looking For

• BS(CS) or MS(Computational Linguistics)
• 5 years’ or more
  

Skills

• Expert knowledge with a scripting language (preference: Python), an object-oriented language (e.g. C++, Java) and a query language (preference: SQL).
• Expert knowledge and Experience of building ML Pipeline Architectures and the general lifecycle of an NLP Project.
• Experience and/or demonstrable knowledge of manual and/or automated data analysis and its techniques for extracting meaningful insights and be able to communicate them effectively.
• Expert knowledge and Experience of working on conventional ML/DL problems like: Supervised Classification and Unsupervised Clustering, as well as some optional knowledge about RL (Reinforcement Learning).
• Expert knowledge and Experience with classic NLP Feature-Extraction techniques such as: n-grams, part-of-speech tagging, semantic distance metrics, search indexing, and corpus analysis etc.
• Expert knowledge and Experience of working on conventional Computational Linguistics problems such as: Syntactic Processing, Word Sense Disambiguation, Context-Free Grammars, Lexical Semantics, Quantification and Plurality, etc.
• Expert knowledge and Experience of working in conventional NLP problems like: Informational Retrieval, Relevance Ranking and Search, Question-Answer Generation, Natural Language Inference, Topic Modeling etc.
• Experience and/or demonstrable knowledge of working in Conversational AI: particularly in its classical NLP problems like: Automatic Speech Recognition (ASR), Machine Translation, Chatbot Response Generation, Frame-wise Spoken Dialogue-Intent Recognition, Dialogue-Act Classification and Slot-Labeling, Turn Allocation and Dialogue State Tracking, etc.
• Optional experience working with both Audio and Text Datasets on spoken language problems.
• Experience working with Deep learning and ML API’s such as Tensorflow, PyTorch, XGboost, CatBoost, etc as well as a firm grip over modern state-of-the-art and otherwise NLP architectures such as BERT, GPT3, Reformer, RNNs, CNNs, LSTMs etc and vector space models such as GloVe, Word2vec, USE etc.
• Ability to communicate technical concepts and solutions at a level appropriate for technical/non-technical audiences.
• Have a decisive personality and ability to utilize past experience to derive ETAs, timelines, resource consumption and realistic result expectations.
• Ability to define and structure project lifecycles: conceptualization, architectural and database design, skeletal construction, task delegation to inter and intra team developers, milestone deliverables and possible improvement tracks.
• Ability to explain and justify research and analysis done for a cause and deliver acquired results to the higher management.
• Ability to point out fallacies / pitfalls in implemented model architectures, algorithms and data processing.
• Ability to understand the goals of the project and the end user and set the right expectations with higher management after analyzing AI and business constraints.
• Experience working with Numerical Computing Tools like: NumPy, SciPy – using the standard Pandas API.
• Experience working with ML/DL frameworks like: Scikit-Learn, Tensorflow, Keras, PyTorch, etc.
• Familiarity with utilizing hardware acceleration concepts and tools such as Numba, PyCuda, TFX Runtime, etc.
• Familiarity with Model Serving APIs like: Tensorflow Serving, TorchServe, Django & Flask, etc.
• Good to haves: Familiarity with Model Serving APIs like: Tensorflow Serving, TorchServe, Django & Flask and Familiarity with Utilizing hardware acceleration concepts and tools such as Numba, PyCuda, TFX Runtime, etc.
  

Job Location:

• Lahore