Senseye is seeking an ML Engineer to help revolutionize Mental Health by building the world's first objective mental health diagnostic platform using NeuroTechnology. The goal is to provide clinicians with a safe and objective approach to identifying and monitoring mental health diseases, addressing unmet medical needs and enabling access to treatment for millions.
Requirements
- 5+ years of applied ML experience, including deploying models to production.
- Expertise in computer vision and/or time-series modeling, with experience in video or camera-based systems strongly preferred.
- Strong statistical modeling skills, particularly in extracting signals from noisy datasets.
- Proficiency in Python and deep learning frameworks (PyTorch, JAX, TensorFlow).
- Proven track record of translating academic research into scalable, practical ML solutions.
- Experience with large-scale data systems, MLOps tooling, and model versioning practices.
- Expert-level proficiency in Python and at least one deep learning framework (PyTorch, JAX, etc.).
Responsibilities
- Design, develop, and deploy ML models focused on computer vision and time-series analysis (e.g., semantic segmentation, point-of-gaze tracking, keypoint detection, photoplethysmography, MAMBA, dilated 1D CNNs, sparse attention transformers).
- Select optimal architectures and training methods that align with constraints around data collection, annotation quality, timelines, and budgets, such as incorporating semi-supervised and few-shot techniques when applicable.
- Develop and maintain robust, production-grade ML services supporting critical user workflows.
- Monitor production model performance, establishing evaluation frameworks that accurately reflect real-world use.
- Conduct comprehensive exploratory data analyses to guide problem scoping, feature engineering, and model selection.
- Collaborate closely with platform and infrastructure teams to optimize ML tooling and data pipelines.
- Translate ambiguous business needs into structured ML problems and actionable technical roadmaps.
Other
- AbilitComfort managing ambiguity and independently driving projects to completion to clearly communicate technical solutions and their business impact to varied audiences.
- Demonstrated creative problem-solving ability, evidenced by patents or novel techniques.
- Experience managing scientific projects within industry or academia.
- Excellent written and verbal communication skills, able to bridge technical and non-technical audiences effectively.
- Familiarity with healthcare, SaMD, or regulated industries, including validation and compliance standards.
