AI Technology Innovator

1 day ago

Noida, Uttar Pradesh, India beBeeDataScience Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Title: Data Science Lead

Ripik.ai is a fast-growing industrial AI SAAS start-up founded by IIT D and BITS alumni with extensive experience in McKinsey, IBM, Google and others. It has partnered with GCP, Azure, AWS and is the AI partner of choice for CII, ICC and NASSCOM.

The company builds patented full stack software for automation of decision making on the factory floor. Today, they are deployed at more than 15 of the largest and most prestigious enterprises in India including market leaders in steel, aluminum, cement, pharma, paints, consumer goods and others.

As Data Science Lead, you will be responsible for leading, mentoring, and growing a team of data scientists and ML engineers. You will design and implement scalable computer vision algorithms and oversee the end-to-end lifecycle of ML projects from data collection and preprocessing to model development, deployment, and monitoring.

You will collaborate with product, engineering, and business teams to translate requirements into data-driven solutions and stay updated with the latest research in AI/ML to apply cutting-edge techniques to solve business problems.

Key Responsibilities:

  • Lead, mentor, and grow a team of data scientists and ML engineers.
  • Design and implement scalable computer vision algorithms (e.g., image recognition, object detection, segmentation, OCR, video analytics).
  • Oversee the end-to-end lifecycle of ML projects from data collection and preprocessing to model development, deployment, and monitoring.
  • Collaborate with product, engineering, and business teams to translate requirements into data-driven solutions.
  • Stay updated with the latest research in AI/ML and apply cutting-edge techniques to solve business problems.

Required Skills & Experience:

  • 5 years of experience into Data Science. Experience as a team lead is preferred.
  • Strong hands-on experience in Computer Vision.
  • Proficiency in Python and libraries such as NumPy, Pandas, scikit-learn, and computer vision toolkits.
  • Solid understanding of cloud platforms (AWS, Azure, GCP) for deploying ML models.
  • Proven track record of building and deploying vision-based AI solutions at scale.

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