Ripik.AI - MLOps Specialist (2-5 yrs)

Overview about Ripik.AI :

Ripik.ai is a fast growing industrial AI SAAS start-up founded by IIT D/ BITS alumni and with extensive experience in McKinsey, IBM, Google and others. It is backed by marquee VC funds like Accel, Venture Highway and 25+ illustrious angels including 14 unicorn founders.

Ripik.ai builds patented full stack softwares 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 the market leaders in steel, aluminum, cement, pharma, paints, consumer goods and others.

It is one of India's very few AI product start-ups to be a partner to GCP, Azure and AWS. We are also the AI partner of choice for CII, ICC and NASSCOM.

About the role :

We are seeking a skilled MLOps specialist. The ideal candidate will bridge the gap between research and deployment, ensuring that data science workflows are both robust and scalable. The role requires expertise in deploying models, maintaining their performance, and conducting cutting-edge research to optimize and innovate for our use cases.

KRAs :

1. Model Deployment & Maintenance :

- Monitor and ensure the reliability of data science workflows and scripts for deployed models.

- Troubleshoot and resolve any downtime or issues in the deployment process.

- Deploy models across edge devices and cloud-based virtual machines.

2. Model Research & Optimization :

- Conduct research to identify and implement state-of-the-art models for specific use cases.

- Optimize models for reduced size and lower memory bandwidth without compromising performance.

- Evaluate and experiment with advanced frameworks and techniques to improve efficiency.

3. Open Source Platform Expertise :

- Utilize platforms such as Hugging Face to access, deploy, and fine-tune models effectively.

- Stay updated on the latest developments in open-source AI communities.

4. Hardware & System Integration :

- Leverage domain knowledge of data science-relevant hardware for optimized model deployment.

- Collaborate with engineering teams to integrate models with production systems seamlessly.

Required Skills :

- Proficiency in Python and a strong understanding of its application in data science workflows.

- Expertise with ONNX and frameworks for model optimization and deployment.

- Hands-on experience with Hugging Face or similar platforms for model research and development.

- Familiarity with visual language models (VLMs) and large language models (LLMs), including their training and deployment frameworks.

- Knowledge of cloud compute services (AWS, GCP, Azure, etc.) and deployment on virtual machines.

- Database management and integration skills.

- Understanding of edge computing and deployment strategies for constrained environments.

Preferred Qualifications :

- Experience: 2+ years as a Data Engineer or Data Scientist with demonstrated success in model deployment and optimization.

- Educational Background: Bachelor's degree in Engineering (BE/BTech) or related fields.

- Experience in training or fine-tuning large models using efficient frameworks.

- Familiarity with GPU/TPU optimization and parallel computing techniques.

- Strong ability to source and synthesize new research from multiple systems and communities.

- Excellent problem-solving skills with a proactive approach to troubleshooting and optimization.