AI Engineer - I/II

3 Hours ago • 7-10 Years

Job Summary

Job Description

This AI Engineer role involves developing NLP algorithms and AI-based computer vision applications. The responsibilities include working with NLP techniques, GenAI techniques, and MLOps. The job requires understanding machine learning techniques, experience in CV based deep learning models, and exploratory data processing techniques. The candidate should be proficient in building and optimizing reactive and predictive models with Machine Learning techniques, and have strong analytical, problem-solving, and communication skills. The role is an office based role.
Must have:
  • Experience in developing NLP algorithms and AI based Computer Vision applications.
  • Experience in NLP techniques for text representation and semantic extraction.
  • Experience in using GenAI techniques like Auto encoders, Transformers, LLMs, RAG.
  • Experience and understanding of MLOps and AI algorithm inferencing.
  • Understanding of machine learning techniques and algorithms.
  • Experience in CV based Deep Learning models.

Job Details

Job Title

AI Engineer - I/II

Job Description

Your role:

  • Experience in developing NLP algorithms, AI based Computer Vision applications

  • Experience in NLP techniques for text representation (such as n-grams, bag of words, sentiment analysis etc), semantic extraction techniques, data structures and modeling

  • Experience in using GenAI techniques like Auto encoders, Transformers, LLMs, RAG Architecture

  • Experience and understanding of MLOps, AI algorithm inferencing and deployments on the Cloud (AWS, Azure or GCP)

  • Excellent understanding of machine learning techniques and algorithms like k-NN, SVM, Random Forest, privacy models, etc.

  • Experience in CV based Deep Learning models like Unet, YOLO etc

  • Understanding exploratory data processing techniques such as cleaning and verifying the integrity of data used for analysis

  • Understanding of state-of-the-art computer vision, NLP and AI for imaging algorithms


You're the right fit if:

  • 7-10 years experience in AI and Data Science field

  • Master's in computers, electronics, electrical engineering or PhD in relevant streams

  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.

  • Experience in building and optimizing reactive and predictive models with Machine Learning techniques

  • Experience with one or more analytic software tools or languages like Python, R

  • Experience with machine learning frameworks, like Keras or PyTorch and Deep Learning based libraries for imaging

  • Strong analytical, problem solving and communication skills



How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.
this role is an office role.

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
• Learn more about our business.
• Discover our rich and exciting history.
• Learn more about our purpose.

If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here.

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About The Company

Over the past decade we have transformed into a focused leader in health technology.

At Philips, our purpose is to improve people’s health and well-being through meaningful innovation. We aim to improve 2.5 billion lives per year by 2030, including 400 million in underserved communities.

We see healthcare as a connected whole. Helping people to live healthily and prevent disease. Giving clinicians the tools they need to make a precision diagnosis and deliver personalized treatment. Aiding the patient's recovery at home in the community. All supported by a seamless flow of data.

As a technology company, we – and our brand licensees – innovate for people with one consistent belief: there’s always a way to make life better.


Visit our website: http://www.philips.com/
Follow our social media house rules https://www.philips.com/a-w/about-philips/social-media.html

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