Enterprise AI infrastructure and deployment at production scale.
Founded
2024
Industry
Enterprise AI / AI Infrastructure
Funding Track Record
Series A- April 2025
$20.0M
Participation from Cisco Investments; brought total disclosed funding to $37.5M
Series A (follow-on)- February 2026
$50M
Follow-on financing bringing total funding to $87.5M; participation from Mayfield, Cisco Investments, Acclimate Ventures, AI Space and other strategic investors
Investor Signal
“Backed by venture investors including Mayfield Fund, Cisco Investments, and Xora Innovation”
Founders
What we do
Join the Team
Senior Software Development Engineer (AI/ML)
On-SiteBengaluru, Karnataka, IN
On-Site • Bengaluru, Karnataka, IN
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About Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
Position Summary
We are seeking a talented Engineer to join our AI team. You will technically lead experienced software and machine learning engineers to develop, test, and deploy AI-based solutions, with a primary focus on large language models and other machine learning applications. This is an excellent opportunity to apply your software engineering skills in a dynamic, real-world environment and gain hands-on experience in cutting-edge AI technology.
Key Responsibilities
Basic Qualifications
A master's degree or PhD in Computer Science, Data Science, Engineering, or a related field
Experience: 5-8 Years
Strong programming skills in Python
Good understanding of machine learning fundamentals
Hands-on experience with Python and common ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
Familiar with frontend development and frameworks like React
Basic knowledge of LLMs and transformer-based architectures is a plus
Preferred Qualifications
Excellent problem-solving skills and an eagerness to learn in a fast-paced environment
Strong attention to detail and ability to communicate technical concepts clearly
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.
Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.
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Design and Develop AI-Powered Solutions: Architect and implement scalable AI/ML systems, focusing on Large Language Models (LLMs) and other deep learning applications.
End-to-End Model Development: Lead the entire lifecycle of AI models—from data collection and preprocessing to training, fine-tuning, evaluation, and deployment.
Fine-Tuning & Customization: Leverage techniques like LoRA (Low-Rank Adaptation) and Q-LoRA to efficiently fine-tune large models for specific business applications.
Reasoning Model Implementation: Work with advanced reasoning models such as DeepSeek-R1, exploring their applications in enterprise AI workflows.
Data Engineering & Dataset Creation: Design and curate high-quality datasets optimized for fine-tuning AI models, ensuring robust training and validation processes.
Performance Optimization & Efficiency: Optimize model inference, computational efficiency, and resource utilization for large-scale AI applications.
MLOps & CI/CD Pipelines: Implement best practices for MLOps, ensuring automated training, deployment, monitoring, and continuous improvement of AI models.
Cloud & Edge AI Deployment: Deploy and manage AI solutions in cloud environments (AWS, Azure, GCP) and explore edge AI deployment where applicable.
API Development & Microservices: Develop RESTful APIs and microservices to integrate AI models seamlessly into enterprise applications.
Security, Compliance & Ethical AI: Ensure AI solutions comply with industry standards, data privacy laws (e.g., GDPR, HIPAA), and ethical AI guidelines.
Collaboration & Stakeholder Engagement: Work closely with product managers, data engineers, and business teams to translate business needs into AI-driven solutions.
Mentorship & Technical Leadership: Guide and mentor junior engineers, fostering best practices in AI/ML development, model fine-tuning, and software engineering.
Research & Innovation: Stay updated with emerging AI trends, conduct experiments with cutting-edge architectures and fine-tuning techniques, and drive innovation within the team.
