Machine Learning Engineer - Graph ML & Code Intelligence

About Us:

IR Labs is the innovation lab inside Integrated Research where small, cross‑functional squads chase outsized, industry‑defining opportunities. We operate like a funded startup - rapid sprints, bold experimentation, zero bureaucracy - backed by the global footprint and resources of a public company. Our charter is simple: turn cutting‑edge AI research into products that customers can’t imagine working without. We target the hardest problems in software and then move fast to ship solutions that create 10x impact.

Our flagship is Agentic SQA - a software quality system that turns noisy signals (static analysis, fuzzers, sanitizers, CI output) into context-aware triage, validated actions, and developer-ready outputs. We’re in beta now, starting narrow on a focused C/C++ risk-analysis workflow targeting a specific bug class, and expanding from there into broader coverage, richer evidence, and stronger control layers. The stack combines LLVM/clang static analysis, a code knowledge graph, and agentic LLM workflows. The direction is bigger than code review: a systems verification platform that closes the gap where human-speed review is breaking down.

If you thrive on autonomy, crave world‑class technical challenges, and want to see your ideas hit production quickly, IR Labs is your launch pad. Join us and help build the future, one breakthrough at a time.

Who We’re Looking For:

Do you see source code as a living graph and get fired up about turning billions of edges into actionable insight? At IR Labs you’ll be the founding Machine Learning Engineer for Graph ML & Code Intelligence. You’ll join a tight, cross functional squad of ML, compiler, and platform experts to build graph native models that untangle the world’s most complex software systems, then ship them to production in weeks, not quarters.

Your mandate is truly end to end: design the graph learning roadmap, stand up high throughput pipelines, fuse GNNs with LLM stacks, and watch your models drive 10× impact for Fortune scale customers.

What You’ll Do:

• 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.

What You Bring to the Table:

• 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.

Our job descriptions often reflect our ideal candidate. If you have a strong foundation of relevant skills and a passion for this field, we encourage you to apply, even if you don't check every box.

What We Offer:

• High Impact: ship real features in weeks, not quarters
• Cutting-Edge Tech: work to solve problems no one has cracked before.
• 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.
• Top-Tier Compensation: competitive salary, performance bonuses, equity upside, and strong benefits.
• Team & Culture: small, senior team that values collaboration, creativity, and building something meaningful together.
• Medical, Dental, Vision Insurance.
• 401k with Employer Contributions.
• Paid Time Off & Birthday Leave.
• Health Savings Account (HSA) Employer Contributions with High-Deductible Health Plan.
• Employer-paid Short-Term/Long-Term Disability Insurance.
• And more!

Compensation Range

• $300,000 - $400,000 base salary
• $80,000 - $120,000 variable compensation

Actual compensation offer to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level. The pay ratio between base pay and target incentive (if applicable) will be finalized at the offer stage.

At IR, we celebrate, support, and thrive on difference for the benefit of our employees, our products, and our community. We are proud to be an Equal Employment Opportunity employer and encourage applications from all suitable candidates; we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status.