Note: The job is a remote job and is open to candidates in USA. IR Labs is an innovation lab within Integrated Research focused on turning advanced AI research into production products. The Machine Learning Engineer will own the graph machine learning roadmap, develop and deploy graph neural networks and graph-language system integrations, and build scalable, reliable graph services and ML/DataOps infrastructure while providing technical leadership and mentoring.
Responsibilities
- Own the graph-ML roadmap end-to-end—turn research into production, balance SOTA with real-world constraints, and champion graph learning across teams
- Design and train modern GNNs/graph transformers; explore self-supervision, sparsity, and pretraining to lift retrieval, grounding, and reasoning
- Build high-performance training/inference pipelines on distributed GPUs with efficient sampling, mixed precision, and custom optimization where needed
- Fuse graphs with language systems to power retrieval and reasoning primitives across the product
- Model complex technical artifacts as graphs (e.g., code/IR or telemetry) and learn over them for analysis and optimization signals
- Ship low-latency, scalable graph services and APIs with streaming updates and robust SLAs
- Benchmark and harden sparse+dense kernels; instrument for performance, correctness, and reliability
- Establish ML/DataOps for large graphs (versioning, lineage, CI/CD) and embed security, privacy, and compliance by design; mentor and uplevel the team
Skills
- 8+ years delivering production ML; 5+ years leading large-scale graph learning in production (100M–B+ edges)
- Deep mastery of GNNs/geometric DL, graph theory, and practical graph querying
- Proven impact combining graphs with LLM/NLP (e.g., KG-augmented retrieval, entity linking, grounding)
- Experience deriving graphs from complex sources (such as code/IR) for analysis, optimization, or security use cases
- Strong systems chops: C++/CUDA or equivalent; fluency in GPU/distributed training and performance tuning
- Track record building reliable pipelines and operating large data/feature stores for graph workloads
- Operational excellence in orchestration, containerization, observability, drift detection, and automated retraining
- Clear, persuasive technical leadership and mentoring across both technical and non-technical stakeholders
Benefits
- Remote & Flexible – Work from anywhere with a culture built on trust, autonomy, and balance.
- Growth & Ownership – Own features end-to-end, learn rapidly, and grow with the company as we scale.
- Performance bonuses
- Equity upside
- Medical, Dental, Vision Insurance.
- 401k with Employer Contributions.
- Paid Time Off & Birthday Leave.
- Health Savings Account (HSA) Contributions with High Deductible Health Plan.
- Short-Term/Long-Term Disability Insurance.
Company Overview
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