Machine Learning Systems Engineer

Job Description:

1. Hands-on with designing end to end scalable ML system

2. Hands-on with the implementation of a scalable ML system.  Proven ownership across the entire or partial ML and MLOps lifecycle:

• Evaluation Techniques
• Machine Learning Algorithms
• Statistical Modeling
• End-to-end deployment
• Metric generation
• Model monitoring and deployment
• Prompt Engineering

3. Hand on with ML Model optimization - quantization, pruning, or speculative decoding, etc.

4. Hand on with ML Model system optimizations ie ability to quickly identify bottlenecks and resolve them from the system perspective

5. Programming & Frameworks: Hands-on experience, and have worked on recent projects 

• Java
• library/dependency management
• Algorithms
• Package and distribution management
• Python
• TensorFlow / PyTorch

6. Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform).

7. Strong understanding of containerization technologies (e.g., Docker, Kubernetes).

Good to have:

• Google Cloud Platform ML Tech stack
• Experienced with Infrastructure as Code (IaC)
• Experience with big data technologies such as Apache Spark or Hadoop.
• Stay informed about the ethical implications of machine learning, e.g., selection bias
• Model Training
• Data Analytics - figure out anomalies, skew, discrepancies
• Hands-on with developing on the Device ML System.

Education: Bachelor''s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

GlobalLogic estimates the starting pay range for this role to be performed in Remote, to be $140,000 to $150,000, and reflects base salary only. This pay range is provided as a good-faith estimate, and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations