PVAR SERVICES Looking For Artificial Intelligence Engineer at Gurugram, Haryana, Full Time

Designation: Artificial Intelligence Engineer

Location: Gurgaon

Salary: Upto 25 LPA

Working: 5 Days

Experience: 4-6 years

𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗕𝗿𝗶𝗲𝗳:

We are hiring for a technology service company that specializes in designing and engineering digital experiences for the government and various industries. Started in 2013, by IIT Roorkee Alumni.

Role and Responsibilities:

– Develop, train, test, and deploy machine learning models using Pytorch / Tensorflow.

– Building Models for tasks like NLP, STT, and TTS.

– Work collaboratively with cross-functional teams to identify business problems and develop machine-learning solutions to solve them.

– Implement and maintain machine learning pipelines to support data ingestion, processing, and transformation.

– Optimize and fine-tune machine learning models to ensure high performance and accuracy.

– Strong understanding of AI fundamentals: The candidate should have a deep understanding of the fundamentals of AI, including machine learning, natural language processing, computer vision, expert systems, and other techniques.

– Programming skills: The candidate should be proficient in at least one programming language, such as Python, Java, C++, or R.

– Knowledge of cloud-based AI platforms: Many companies are moving towards cloud-based AI platforms such as AWS, Azure, and Google Cloud. The candidate should have experience with at least one of these platforms and be comfortable working with cloud-based services.

– Data analysis and data engineering: The candidate should be skilled in data analysis and data engineering techniques, which are essential for building effective AI models.

– Stay up-to-date with the latest trends and developments in machine learning, deep learning, and artificial intelligence.

Skills Required:

– Minimum of 4 years of experience as a Machine Learning Engineer or a similar role.

– Strong programming skills in Python and experience with Pytorch and TensorFlow.

– Experience with data pre-processing, feature engineering, and data analysis.

– Should have worked extensively on Deep Neural Network

– Should have experience with Models like GAN, Conditional GAN, Transformers, etc

– Should have used/exposed with Stable Diffusion, Latent Diffusion, InPainting, Text-to-Image Model, Image-to-Image Model, etc

– Strong understanding of machine learning algorithms and techniques, such as deep learning, supervised and unsupervised learning, reinforcement learning, and natural language processing.