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Lead Research Engineer (AI/ML, NLP, Systems)
Remote / Hybrid (US-based)
We’re hiring a Lead Research Engineer to help build and scale next-generation AI systems that transform how professionals work with complex information.
This is a high-impact role at the intersection of applied research and production engineering—ideal for someone who enjoys taking cutting-edge ideas and turning them into scalable, real-world systems.
What You’ll Do
- Lead technically: Define engineering standards, shape architecture, and mentor engineers across ML initiatives
- Build end-to-end ML systems: From data pipelines → model development → deployment → monitoring
- Develop scalable infrastructure: Design high-performance systems for training and serving ML models in production
- Collaborate cross-functionally: Work closely with research scientists, product teams, and distributed engineering teams
- Drive innovation: Prototype new approaches and bring them into production environments
- Own delivery: Take responsibility for shipping robust, scalable solutions
What We’re Looking For
- 8+ years of software engineering experience, with strong exposure to machine learning systems
- Deep expertise in Python and the ML ecosystem (NumPy, Pandas, PyTorch, scikit-learn, etc.)
- Proven experience building and deploying ML systems at scale
- Strong understanding of MLOps / ModelOps, including monitoring, automation, and lifecycle management
- Experience designing data pipelines and working with large-scale data processing frameworks
- Familiarity with cloud platforms (AWS, Azure, or similar) and distributed systems
Background in Natural Language Processing (NLP), including areas like:
- Information Extraction
- Named Entity Recognition (NER)
- Information Retrieval
- Ability to translate research into production systems
- Experience mentoring engineers and leading technical workstreams
Nice to Have
- Experience with knowledge graphs, LLMs, or advanced NLP systems
- Exposure to additional languages (Java, TypeScript, etc.)
- Strong grounding in probabilistic models and ML theory
Why This Role
- Work on high-impact AI systems applied to complex, real-world domains
- Collaborate with a global, interdisciplinary team of engineers and researchers
- Solve problems where data quality, scale, and accuracy truly matter
- Own systems end-to-end—not just models, but the infrastructure around them
If you’re excited about building production-grade AI systems and leading from the front, we’d love to connect.
