R&D Technical Lead
About the role
We are seeking an experienced R&D Technical Lead to bridge the gap between AI/ML research and production-ready solutions. In this role, you will provide technical leadership across AI/ML and software engineering, guiding teams from early-stage research concepts through successful customer delivery. The ideal candidate brings a broad software engineering background combined with strong AI/ML expertise, with the ability to translate machine learning models and research into scalable, integrated software architectures. You will collaborate across disciplines to drive technical decisions, mentor development teams, and ensure solutions meet real-world customer needs.
Our work focuses on applied AI/ML solutions for real-world object tracking, detection, and characterization, enabling advanced data triaging and system automation. These capabilities help our customers manage increasing volumes of data and address the challenges associated with data saturation.
Responsibilities
- Provide technical guidance to engineering teams, aligning project requirements to technical tasking
- Design and implement scalable, high-performance software systems that integrate AI/ML capabilities
- Architect multi-agent or agentic workflows to synchronize data collection efforts across various projects, optimizing resource allocation
- Lead a high-performing team of engineers, conducting code reviews and setting engineering standards for MLOps and production pipelines
- Collaborate with project managers to translate complex client requirements into actionable AI/ML roadmaps
Requirements
- Bachelor’s or above in Computer Science, AI, or a related quantitative field
- 7+ years of professional experience in machine learning, with at least 3 years leading teams from research or prototyping through production deployment
- Proven track record in developing computer vision models for object tracking (e.g., CNNs, Transformers) and real-time video analytics
- Expert-level proficiency in Python and high-performance languages (C++/Rust/Java) alongside familiarity with backend deployment tools (Docker, Kubernetes)
- Experience overseeing the full data lifecycle, from acquisition and cleaning to high-fidelity labeling for specialized collections
- Ability to articulate complex AI concepts to non-technical stakeholders and executive leadership