Skit.ai Off Campus Hiring 2024 – Software Engineer – Solutions – Apply Now! | Apply Now

  • Full Time
  • Bangalore, India
  • INR 10 – 12 LPA(Estimated) INR / Year

 skit.ai

Skit.ai Off Campus Hiring 2024 – Software Engineer – Solutions Role. Interested Candidates can go through the details and apply using the link provided at the bottom of the Post.

Skit.ai Off Campus Hiring 2024 – Software Engineer – Solutions

Company name  skit.ai
Website www.skit.ai
Job Role Software Engineer – Solutions
Work Location Bangalore, India
Job Type Full Time
Experience 0-2 Years
Qualification A degree in Computer Science, Machine Learning, Artificial Intelligence, or a similar discipline (Bachelor’s, Master’s, or PhD).
Batch Not Mentioned
Package INR 10 – 12 LPA(Estimated)

Job Description

Job Summary

As a Data Scientist, you will collaborate with teams from various disciplines, such as Technical Art, Software Engineering, and Product Management. Your role will involve developing and refining machine learning models and computer vision solutions, followed by their deployment and maintenance in production environments.

Key Responsibilities:

  • Support the creation, deployment, and optimization of machine learning models and algorithms, focusing on object detection and computer vision.
  • Work closely with cross-functional teams to understand project goals and contribute to building effective solutions.
  • Stay updated on the latest advancements in machine learning and computer vision, conducting research to integrate cutting-edge techniques.
  • Evaluate model performance, suggest improvements, and ensure model accuracy and efficiency.
  • Document and present findings, progress, and insights to both technical and non-technical audiences.

Qualifications:

  • A degree in Computer Science, Machine Learning, Artificial Intelligence, or a similar discipline (Bachelor’s, Master’s, or PhD).
  • Proficiency in computer vision models, including modern architectures like YOLO and transformer-based models such as ViT and BLIP.
  • Strong foundation in machine learning and deep learning, with hands-on experience in Python and machine learning libraries like TensorFlow, PyTorch, or Keras.
  • Experience with data processing tools like Pandas and NumPy.
  • Excellent problem-solving skills, with a creative approach to overcoming challenges.
  • Effective communication and teamwork abilities, capable of collaborating in cross-functional settings.
  • A proactive learner, passionate about keeping up with recent developments in machine learning and computer vision.
  • A self-driven, detail-oriented individual who thrives in ambiguous situations.
  • A desire to contribute positively to a collaborative and inclusive work culture.

How to Apply?

  • To apply for a job, read through all information provided on the job listing page carefully.
  • Look for the apply link on the job listing page, usually located somewhere on the page.
  • Clicking on the apply link will take you to the company’s application portal.
  • Enter your personal details and any other information requested by the company in the application portal.
  • Pay close attention to the instructions provided and fill out all necessary fields accurately and completely.
  • Double-check all the information provided before submitting the application.
  • Ensure that your contact information is correct and up-to-date, and accurately reflect your qualifications and experience.
  • Submitting an application with incorrect or incomplete information could harm your chances of being selected for an interview.

About Skit.ai

Skit.ai is an advanced conversational AI platform designed to automate customer interactions, particularly in the contact center space. It uses voice AI technology to streamline and enhance customer service by handling routine queries and tasks through natural language conversations. Skit.ai helps businesses reduce operational costs, improve response times, and boost customer satisfaction by automating repetitive tasks, allowing human agents to focus on more complex issues. With its scalable and adaptive system, it is increasingly being adopted across industries like banking, insurance, and e-commerce.

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