ML Systems Engineer

Company Description

Healthpoint Ventures is dedicated to driving innovation in healthcare by using artificial intelligence to enhance value across the healthcare ecosystem. Through strategic investments and partnerships, we focus on advancing care delivery and improving operational efficiency. Our experienced global team specialises in AI product development and technology, creating tailored solutions to address the unique challenges of the healthcare industry. From optimising workflows to revolutionising care models, we offer comprehensive services in AI strategy and implementation. Our mission is to transform healthcare by leveraging AI for better clinical outcomes, efficient operations, and innovative care solutions.

Role Description

This is a full-time on-site role for a Machine Learning (ML) Systems Engineer, located in Gurugram. The ML Systems Engineer will design, develop, and implement machine learning systems, ensuring optimal performance and reliability. Key responsibilities include systems engineering, troubleshooting, and providing technical support for deployed systems. The role also involves system administration, managing infrastructure, and collaborating with cross-functional teams to design and improve system performance.

**Responsibilities**

- Adapt optimisation loop for AMD (ROCm PyTorch)

- Implement configuration generator (hyperparameter search space)

- Build a simple Bayesian optimisation loop (can use Optuna or Ax)

- Implement parallel job submission (50-100 configs)

- Collect results and compute the Pareto frontier

- Support 2-3 pre-defined models (Llama-3-8B, Mistral-7B, Qwen-7B)

**Key Simplifications**:

- Use existing open-source optimiser (Optuna) instead of building custom

- Pre-define search space (don't let users customise)

- Limit to single optimisation objective initially (accuracy vs speed)

- Skip compression techniques for v1 (focus on training/inference optimisation)

Qualifications

• Advanced skills in Systems Engineering and Systems Design
• Experience with Troubleshooting and Technical Support
• Proficiency in System Administration and managing system infrastructure
• Knowledge of Machine Learning technology and its practical implementation
• Excellent problem-solving and critical-thinking skills
• Ability to work collaboratively in a dynamic and fast-paced environment
• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• Familiarity with healthcare-specific AI applications is a plus