The Role
As the AI Team/ML Research Lead at Blackrock, you will define and drive the next generation of machine learning systems powering brain-computer interface (BCI) technology. This role exists to translate cutting-edge AI research into real-world, high-impact systems capable of decoding complex neural signals in real time. You’ll lead both the technical direction and a team of researchers, shaping architectures that learn robust, generalizable representations from highly complex and heterogeneous brain data.
Success in this role looks like delivering scalable, production-ready AI systems, accelerating innovation at the intersection of machine learning and neuroscience, and enabling breakthroughs that directly expand human capability. This is a highly collaborative role, partnering closely with neuroscience, hardware, data and clinical teams to bring research into deployment. You will operate with meaningful ownership in a high-consequence environment, contributing to systems that must be precise, reliable, and durable.
The Impact You'll Make
In this role, you will directly influence the future of neurotechnology by building AI systems that power life-changing BCI applications. Your work will shape how neural data is interpreted and translated into meaningful outputs, ultimately impacting patient outcomes and redefining what’s possible in human computer interaction.
Internally, you will elevate the AI/ML function by setting technical standards, mentoring talent, and establishing a high-performance, research-driven culture that attracts and retains top-tier talent.
What You'll Do
- Lead the design, development, and deployment of advanced AI/ML systems for brain-computer interface applications
- Drive technical strategy and architecture decisions for complex, large-scale machine learning systems
- Build and mentor a high-performing AI/ML research team, fostering a culture of curiosity, rigor, and ownership
- Establish and execute roadmaps for AI/ML development, aligning with cross-functional priorities
- Translate cutting-edge research into scalable, real-time neural decoding systems
- Collaborate cross-functionally with neuroscience, hardware, data, and clinical teams
- Communicate critical dependencies, risks, milestones, and key technical decisions to stakeholders
- Continuously push the boundaries of model performance, scalability, and real-world applicability
What You Bring
Minimum Qualifications
- 8+ years of experience in AI/ML, or PhD in a related field with 3+ years of applied experience
- 3+ years of experience leading research or applied machine learning teams
- Deep expertise in sequence modeling architectures, cross-attention mechanisms, and modern training paradigms
- Strong understanding of AI scaling laws, including designing and executing experiments to inform architecture decisions
- Proficiency with modern ML tooling, infrastructure, and compute systems
- Excellent communication skills with the ability to translate complex technical concepts across audiences
Preferred Qualifications
- Experience in neural signal processing, brain-computer interfaces, or bio signal decoding
- Background in cross-domain transfer learning or multi-task learning
- Strong intuition for balancing rapid experimentation with long-term architectural decisions
- Experience with model optimization techniques such as distillation, quantization, and edge deployment
- Familiarity with regulatory considerations for AI and software in healthcare environments
- Proven ability to attract, mentor, and retain top ML talent in a high-autonomy, high-performance environment
- Passion for building AI systems that directly improve patient outcomes
How We Work