Note: The job is a remote job and is open to candidates in USA. Comtech Global, Inc is seeking a highly experienced Machine Learning Engineer to lead the development of production-grade graph machine learning systems. The role owns the graph ML roadmap, translates research into scalable solutions, and works across graph learning, GNNs, graph transformers, LLMs, code intelligence, distributed GPU systems, and large-scale data infrastructure.
Responsibilities
- Own the graph ML roadmap from research through production
- Design and train modern GNNs and graph transformers
- Explore self-supervised learning, sparsity, and pretraining techniques
- Improve retrieval, grounding, reasoning, and other AI capabilities through graph learning
- Build high-performance training and inference pipelines on distributed GPU infrastructure
- Optimize GPU workloads using efficient sampling, mixed precision, and custom optimization techniques
- Combine graphs with LLM/NLP systems to enable retrieval and reasoning capabilities
- Model complex technical artifacts such as source code, intermediate representations (IR), and telemetry as graphs
- Build scalable, low-latency graph services and APIs with streaming updates and strong SLAs
- Benchmark and optimize sparse and dense computational kernels
- Establish ML/DataOps practices for large-scale graph workloads, including versioning, lineage, CI/CD, and automated retraining
- Implement security, privacy, reliability, and compliance practices throughout the ML lifecycle
- Mentor engineers and provide technical leadership across the organization
Skills
- 8+ years of experience delivering production machine learning systems
- 5+ years leading or building large-scale graph ML systems in production
- Experience working with graphs containing 100M to billions of edges
- Deep expertise in GNNs, geometric deep learning, graph theory, and graph querying
- Strong experience combining graphs with LLMs/NLP, including knowledge-graph-augmented retrieval, entity linking, grounding, or related techniques
- Experience deriving graphs from complex technical sources such as code, IR, telemetry, or software dependency data
- Strong systems programming experience with C++/CUDA or equivalent
- Deep understanding of GPU computing, distributed training, and performance optimization
- Experience building reliable ML pipelines and operating large-scale data or feature stores
- Strong experience with orchestration, containerization, observability, drift detection, and automated model retraining
- Excellent technical leadership, communication, mentoring, and cross-functional collaboration skills
- Experience with code intelligence, program analysis, or software security
- Experience with graph databases or graph processing frameworks
- Experience with large-scale distributed graph processing
- Experience optimizing CUDA/GPU kernels
- Experience with knowledge graphs and retrieval-augmented generation
- Experience deploying ML systems with strict latency and reliability requirements
- Experience working in fast-moving AI/ML product environments
Benefits
- Remote & Flexible: Work from anywhere with a culture built on trust and autonomy.
- Own projects end-to-end and grow with the company.
- Medical, Dental & Vision Insurance.
- 401(k) with Employer Contributions.
- Paid Time Off & Birthday Leave.
- HSA Contributions with a High-Deductible Health Plan.
- Short-Term & Long-Term Disability Insurance.
- Additional benefits and perks.
Company Overview
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