Applied Data Scientist


50LPA - 60LPA

Min Experience

2 years





About the role


Company name: Galileo | HQ Location: San Francisco, California | Website | LinkedIn


Role: Applied Data Scientist 

  • Salary: Rs. 50-60 Lakhs per year
  • Experience: 2+ years
  • Location: Bangalore
  • Type: Full-time


Role Description:

As an Applied Data Scientist at Galileo, you will be at the forefront of deploying and customizing advanced generative AI technologies for a diverse set of customers. Your role involves a dynamic combination of technical expertise and customer engagement, where you will work closely with customers to understand their unique AI challenges and deliver tailored solutions.


Leveraging cutting-edge tools like retrieval augmented generation (RAG), large language models (LLM), and Galileo's proprietary technologies, you will develop, optimize, and integrate AI systems that drive significant improvements in customer workflows and decision-making processes.


In this role, you will also play a critical part in the iterative improvement of our technologies through continuous feedback and performance monitoring. You will provide expert-level support, troubleshoot and resolve issues, and conduct training sessions to empower users with the tools and knowledge needed to maximize the benefits of Galileo’s solutions. Your contributions will directly influence product strategy and development, ensuring that our solutions remain at the leading edge of industry standards and client expectations.


Main Responsibilities:

  1. Collaborate Closely with Customers: Engage directly with Galileo's customers to deliver solutions that address their specific generative AI challenges. This involves understanding their unique needs and proposing tailored applications of Galileo’s technologies.
  2. Implement Advanced ML Techniques: Work hands-on with state-of-the-art machine learning technologies, including retrieval augmented generation (RAG), agents, tools, and other cutting-edge LLM technologies, to enhance customer applications.
  3. Develop and Optimize LLMs: Build, train, and refine large language models such as Llama and Mistral tailored for Galileo's users. Utilize the Galileo platform to enhance the performance and efficiency of these models, ensuring they meet specific customer requirements.
  4. Continuous Feedback: Establish a continuous improvement loop by gathering user feedback, monitoring system performance, and making necessary adjustments to models and solutions. This ensures the solutions remain effective and aligned with user needs.
  5. Integration and Workflow Optimization: Assist in the seamless integration of Galileo technologies into customer workflows, ensuring that the solutions enhance operational efficiency and are easy to adopt.
  6. Support and Troubleshooting: Provide expert technical support to customers, helping to troubleshoot issues and optimize the performance of deployed solutions. This includes responding to inquiries, diagnosing problems, and offering immediate solutions or workarounds.
  7. Educate and Train Users: Conduct training sessions and workshops for customers to help them understand and effectively use Galileo’s products. This also involves creating documentation and resources that facilitate easier adoption and usage of the platform.
  8. Contribute to Product Strategy: Provide insights and feedback from customer experiences to the product development teams to inform future product enhancements and new features. This role acts as a bridge between customer needs and the technical capabilities of Galileo.


Minimum Qualifications:

  1. Education: Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
  2. Experience: At least 2 years of relevant work experience in utilizing deep learning frameworks such as PyTorch, TensorFlow, or Keras to address product or business challenges.
  3. Technical Skills: Proficiency in statistical analysis and data science methodologies using Python, R, or SQL. Demonstrable experience in building and optimizing machine learning models.


Preferred Qualifications:

  1. Advanced Degree: Master’s or Ph.D. in Data Science, Machine Learning, Computer Science, or a related field.
  2. Specialized Experience: Experience with large language models (LLMs) and technologies such as retrieval augmented generation (RAG) or similar ML models in production environments.
  3. Industry Knowledge: Prior experience in implementing AI solutions in real-world applications, particularly in sectors relevant to Galileo's client base.
  4. Project Management: Strong project management skills with a proven track record of leading projects from conception to implementation.
  5. Communication Skills: Excellent communication and interpersonal skills, capable of explaining complex technical details to non-technical stakeholders and conducting effective training sessions.


Why Galileo:

  1. Join a seasoned founding team that has previously led product and engineering teams from 0 to $100M+ in revenue and from 0 to 1B+ users globally.
  2. We obsess over our team’s culture driven by inclusivity, empathy and curiosity
  3. We invest in our team’s development and happiness because our employees are the keys to our success and ensuring happy customers – towards that end, we offer:

-Unlimited PTO

-Parental leave – 100% pay for 8 weeks

-Medical, Dental and Vision Insurance

-401 (K) Retirement Savings Plan

-Early stage equity

-Mental and Physical Wellness Stipend

-Daily Lunch Stipend

About the company

About us

At Galileo we are building the first algorithm-powered LLMOps Platform for the enterprise.

Galileo is currently powering ML teams across the Fortune 500 as well as startups across multiple industries.

If you are interested in working at the intersection of Machine Learning and data, alongside industry and academic veterans at a well-funded early stage company going after a big, real and massively underserved problem, we are currently hiring for multiple positions.


Founder/Recruiter profiles:

Vikram Chatterji  


Large language models - LLM