Job Title: ML Benchmarking Engineer

Location: Bangalore

Job Type: Full Time

Education: Bachelors or Masters degree in Computer Science, Electronics, Electrical Engineering, Artificial Intelligence, Machine Learning, Embedded Systems, or a related field.

NP: Serving Notice Period Candidates Preferred

Job Summary:

We are seeking an ML Benchmarking Engineer with hands-on experience in evaluating and benchmarking machine learning models on hardware platforms. The ideal candidate will have a strong background in AI/ML, embedded systems, and performance optimization, along with experience working on hardware accelerators, custom SoCs, and neural processing platforms.

The role involves benchmarking ML models, developing automation frameworks, optimizing evaluation pipelines, and collaborating with cross-functional teams to ensure efficient deployment and performance analysis of AI workloads on embedded and hardware platforms.

Key Responsibilities:

- Benchmark and evaluate machine learning models on hardware platforms.

- Analyze model performance, resource utilization, latency, throughput, and accuracy metrics.

- Work with embedded, MCU, DSP, and hardware accelerator platforms for ML deployment and performance validation.

- Develop and maintain test automation frameworks for ML model evaluation.

- Build and optimize CI/CD pipelines for benchmarking and validation workflows.

- Support model and data ingestion workflows across multiple environments.

- Collaborate with AI/ML, software, hardware, and validation teams to identify and resolve performance bottlenecks.

- Perform debugging, root-cause analysis, and performance optimization of ML workloads.

- Document benchmarking methodologies, results, and best practices.

Mandatory Skills:

ML Model Benchmarking:

- Minimum 3+ years of experience benchmarking ML models on hardware platforms.

- Experience evaluating AI/ML models for performance, scalability, and efficiency.

- Experience working on embedded, MCU, DSP, or hardware-based AI platforms.

- Hands-on experience with platforms such as Turing and HTP (Hexagon Tensor Processor).

Programming Skills:

- Strong proficiency in Python.

- Good experience in C and C++.

Machine Learning Frameworks:

- Hands-on experience with:

1. PyTorch

2. TensorFlow

3. Or similar machine learning frameworks

Hardware Platform Exposure:

- Experience working with:

1. Hardware accelerators

2. Custom SoCs

3. Neural processing platforms

- Understanding of ML deployment on embedded and hardware platforms.

Test Automation:

- Experience developing or maintaining test automation frameworks.

- Experience automating ML model evaluation and benchmarking workflows.

CI/CD & Workflow Automation:

- Experience building and optimizing CI/CD pipelines.

- Experience supporting model and data ingestion workflows.

Required Skills:

- 3+ years of experience in benchmarking ML models on hardware platforms.

- Proficiency in Python and C/C++.

- Hands-on experience with PyTorch, TensorFlow, or similar ML frameworks.

- Experience working with hardware accelerators and custom SoCs.

- Strong debugging and problem-solving abilities.

- Excellent teamwork and communication skills.

Preferred Experience:

- Experience with embedded AI, edge AI, or DSP-based ML deployments.

- Exposure to performance optimization and profiling tools.

- Familiarity with AI inference acceleration technologies.

- Experience working in cross-functional hardware and software development environments.

Benefits:

- Competitive compensation package.

- Opportunity to work on advanced AI and embedded hardware platforms.

- Exposure to cutting-edge machine learning technologies.

- Collaborative and innovative work environment.

- Career growth and learning opportunities.