3+ Natural Language Processing (NLP) Jobs in Coimbatore | Natural Language Processing (NLP) Job openings in Coimbatore
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Responsibilities
- Design and implement advanced solutions utilizing Large Language Models (LLMs).
- Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions.
- Conduct research and stay informed about the latest developments in generative AI and LLMs.
- Develop and maintain code libraries, tools, and frameworks to support generative AI development.
- Participate in code reviews and contribute to maintaining high code quality standards.
- Engage in the entire software development lifecycle, from design and testing to deployment and maintenance.
- Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility.
- Possess strong analytical and problem-solving skills.
- Demonstrate excellent communication skills and the ability to work effectively in a team environment.
Primary Skills
- Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities.
- Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and Huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization.
- Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred.
- Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.
- Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation.
- Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.
Job Description:
1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
b. Improve Model accuracy to deliver greater business impact
c.Estimate business impact due to deployment of model
2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines
4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch
5.Experience in using Deep learning models with text, speech, image and video data
a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
c.Knowledge of State of the art Deep learning algorithms
6.Optimize and tune Deep Learnings model for best possible accuracy
7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau
8.Work with application teams, in deploying models on cloud as a service or on-prem
a.Deployment of models in Test / Control framework for tracking
b.Build CI/CD pipelines for ML model deployment
9.Integrating AI&ML models with other applications using REST APIs and other connector technologies
10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.
· Technology/Subject Matter Expertise
- Sufficient expertise in machine learning, mathematical and statistical sciences
- Use of versioning & Collaborative tools like Git / Github
- Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
- Develop prototype level ideas into a solution that can scale to industrial grade strength
- Ability to quantify & estimate the impact of ML models.
· Softskills Profile
- Curiosity to think in fresh and unique ways with the intent of breaking new ground.
- Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
- Ability to think ahead, and anticipate the needs for solving the problem will be important
· Ability to communicate key messages effectively, and articulate strong opinions in large forums
· Desirable Experience:
- Keen contributor to open source communities, and communities like Kaggle
- Ability to process Huge amount of Data using Pyspark/Hadoop
- Development & Application of Reinforcement Learning
- Knowledge of Optimization/Genetic Algorithms
- Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
- Optimize and tune deep learning model for best possible accuracy
- Understanding of stream data processing, RPA, edge computing, AR/VR etc
- Appreciation of digital ethics, data privacy will be important
- Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
- Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
Job Description:
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- At least 2 years of experience in computer vision and or deep learning for object detection and tracking along with semantic or instance segmentation either in the academic or industrial domain.
- Experience with any machine deep learning frameworks like Tensorflow, Keras, Scikit-Learn and PyTorch.
- Experience in training models through GPU computing using NVIDIA CUDA or on the cloud.
- Ability to transform research articles into working solutions to solve real-world problems.
- Strong experience in using both basic and advanced image processing algorithms for feature engineering.
- Proficiency in Python and related packages like numpy, scikit-image, PIL, opencv, matplotlib, seaborn, etc.
- Excellent written and verbal communication skills for effectively communicating with the team and ability to present information to a varied technical and non-technical audiences.
- Must be able to produce solutions independently in an organized manner and also be able to work in a team when required.
- Must have good Object-Oriented Programing & logical analysis skills in Python.