ML Engineer, Context Integration

Echo Neurotechnologies • San Francisco, CA

18d

About The Position

Echo Neurotechnologies is an exciting new startup in the Brain-Computer Interface (BCI) space, driving innovation through advanced hardware engineering and AI solutions. Our mission is to deliver cutting-edge technologies that restore autonomy to people living with disabilities and improve their quality of life. Join a small, dedicated team of knowledgeable and motivated professionals. Our early-stage environment offers the opportunity to take ownership of broad decisions with significant and long-lasting impact. We emphasize continuous learning and growth, fostering cross-functional collaboration where your contributions are vital to our success. We are seeking an experienced ML Engineer to join our team. The person who fills this role will apply ML & AI principles and practices to multimodal models that can flexibly incorporate information from a variety of sources to power product pipelines and have real-world impact on patients with physical disabilities.

Requirements

• Bachelor's or Master's degree in Math, Engineering, Data Science, or other relevant quantitative field
• A minimum of 5 years of combined academic and professional ML experience
• Experience working with speech-recognition models and LLMs
• Experience deploying ML models in an industry setting
• Proficiency in Python and PyTorch
• Proficiency in using GPUs and GPU software toolkits to accelerate ML pipelines

Nice To Haves

• Experience working with high-dimensional time-series datasets
• Experience working on medical or clinical applications
• Experience with video-processing and application-parsing models
• Experience developing foundation models and applying transfer-learning techniques

Responsibilities

• Designing and building ML pipelines capable of performing flexible, real-time inference with multiple input streams
• Deploying custom or off-the-shelf state-of-the-art models for parsing audio, video, and application states
• Performing context engineering to aggregate and model contextual information for use in downstream decoders
• Model dissection and interpretability to extract information-rich latent representations from large models (e.g. pretrained LLMs) for broad and generalized use in other models
• Model miniaturization for low-latency and computationally inexpensive processing
• Working collaboratively within a small team to explore and iterate on models, design the company's data-science platforms, and integrate ML models into product applications
• Maintaining versioned, clear, and highly documented code, analysis pipelines, and results for maximum interpretability and reproducibility
• Contribute to documentation for a Quality Management System, as appropriate and relevant to ML implementations that become part of medical products

Benefits

• An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment.
• Competitive compensation, including stock options.
• Comprehensive benefits package.
• 401(k) program with matching contributions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level