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Director of Machine Learning
Director of Machine LearningSenseye • Austin, TX, US
Director of Machine Learning

Director of Machine Learning

Senseye • Austin, TX, US
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Senseye is seeking a Director of Machine Learning to lead the design, deployment, and evolution of our ML systems powering the world’s first objective mental health diagnostics platform. This role is both strategic and hands-on : you’ll define the vision and processes for our ML organization while also contributing directly to model development, experimentation, and deployment.

You’ll lead a small but growing team of ML engineers and scientists working at the intersection of computer vision, time-series analysis, and cognitive neuroscience. You’ll establish best practices for reproducibility, evaluation, and experimentation — transforming research concepts into robust, clinically validated production systems. You’ll work closely with leadership to define roadmaps, resource needs, and decision frameworks that are grounded in data and operational transparency.

This role is ideal for a technical leader who thrives in ambiguous, high-stakes environments, enjoys building teams and systems from the ground up, and wants to directly influence how ML is used to transform mental health diagnostics.

Responsibilities

  • Own and drive the ML technical roadmap, balancing short-term delivery with long-term research and infrastructure investments.
  • Design, develop, and deploy models for computer vision and time-series applications (e.g., semantic segmentation, point-of-gaze tracking, keypoint detection, photoplethysmography, MAMBA, dilated 1D CNNs, sparse attention transformers).
  • Lead and mentor a small, high-performing team of ML engineers and scientists; establish technical rigor, code quality, and experimentation culture.
  • Implement reproducible ML processes — from dataset versioning and model tracking (e.g., Weights & Biases) to GPU scheduling, experiment orchestration, and results documentation.
  • Develop and enforce objective evaluation frameworks to assess model performance and reliability across development and production environments.
  • Build transparency and accountability through clear reporting of model metrics, data quality, and production outcomes to both technical and executive audiences.
  • Collaborate cross-functionally with product, clinical, and platform teams to align ML outputs with product goals, user impact, and regulatory requirements.
  • Guide operational planning for ML compute resources, infrastructure scaling, and data pipeline optimization.
  • Translate ambiguous problems into clear ML problem statements, balancing technical feasibility, scientific value, and business impact.
  • Stay ahead of emerging research and tools, integrating new approaches thoughtfully when they advance clinical accuracy, scalability, or efficiency.
  • Represent ML leadership externally, ensuring Senseye’s technical excellence and ethical standards are visible in publications, presentations, and collaborations.

About Us

Senseye is a NeuroTechnology Company in Austin, TX on the cusp of revolutionizing Mental Health. Over the past 6 years we have invested millions of dollars in R&D to build our platform allowing us to measure cognitive activity via the eye through mobile phones. Through multiple iterations and use cases we are now focused on building the world's first objective mental health diagnostic on top of our core technology. Our first diagnostic is for PTSD and is entering clinical trials now, followed soon by additional indications for Anxiety and Depression. As the world struggles with a mental health crisis, it is not hyperbolic to suggest that an objective diagnostic platform, that gives clinicians a safe and objective accurate approach to identifying and monitoring mental health disease, will redefine how mental health services are provided, and will enable access to treatment for millions of sufferers. The Senseye platform has the potential to be the technology that drives this change. This is a great opportunity to shape the future of digital medicine and address unmet medical needs that affect billions of people worldwide.

Hiring Process

Our interview process is designed to evaluate both your technical depth and your fit as a collaborative leader within our mission-driven team.

  • Initial Phone Screening – A short introductory conversation to discuss your background, interests, and alignment with Senseye’s mission and the Director of ML role.
  • Brief Online Technical Assessment – A quick, focused evaluation consisting of a few ML-specific questions to help us understand your problem-solving approach and foundational understanding.
  • Technical Interviews – Two back-to-back interviews, each with two interviewers, covering your technical expertise, applied ML experience, leadership approach, and ability to reason through practical challenges.
  • Advisor Interview – A discussion with one of Senseye’s ML Advisors, focusing on your depth of understanding in machine learning systems, experimentation rigor, and how you approach the frontier of applied AI research.
  • Final Interview – A closing conversation with David Zakariaie, CEO, to align on vision, leadership philosophy, and how you’ll help shape the next phase of Senseye’s ML evolution.
  • We expect the process to take approximately 3–4 weeks from initial contact to decision. We plan to begin interviewing in mid November and aim to make an offer by early to mid-December.

    Requirements

  • 7+ years of applied ML experience, including at least 2+ years in a leadership or staff-level role.
  • Proven success deploying ML models to production and maintaining their performance over time.
  • Expertise in computer vision and / or time-series modeling, ideally within video, camera-based, or biosignal contexts.
  • Strong foundation in statistical modeling and signal extraction from noisy data.
  • Proficiency in Python and at least one major deep learning framework (PyTorch, JAX, TensorFlow).
  • Experience building ML systems in healthcare or regulated environments, with understanding of validation, auditability, and compliance processes.
  • Demonstrated ability to define and communicate objective metrics, build dashboards or reports, and translate results for technical and non-technical audiences.
  • Familiarity with MLOps tooling (e.g., Weights & Biases, MLflow), experiment tracking, and infrastructure management.
  • Strong organizational and planning skills — able to manage GPU resources, schedule experiments efficiently, and prioritize workloads across the team.
  • Exceptional written and verbal communication skills, with a focus on clarity, transparency, and collaboration.
  • Extra Points

  • Experience leading ML teams in production settings, including roadmap development and hiring.
  • Experience integrating ML within SaMD or clinical research pipelines.
  • Track record of adapting cutting-edge research into production-ready methods.
  • Contributions to open-source ML frameworks or published research.
  • Experience with probabilistic modeling or Bayesian inference.
  • Prior experience implementing metrics-driven decision frameworks across teams.
  • Benefits

  • The salary for this position will be between $200,000 and $300,000 a year depending on if the candidate meets all of the requirements as well as the items listed under extra points
  • The freedom and trust to define your role as we design, build, and ship our products
  • Competitive salary and stock option plan
  • Flexible paid time off (vacation, sick leave, and public holidays)
  • Flexible schedules
  • Company health care plan
  • Medical, dental, and vision insurance
  • Short and long term disability insurance
  • Life insurance policy
  • 401k
  • Commuter benefits for parking, public transit, carshares, etc.
  • Mothers' room
  • Fully stocked kitchen
  • Opportunities for continuing education
  • Senseye is dedicated to building a community of employees that are diverse, passionate, and engaged. We are committed to equal opportunity regardless of race, color, ancestry, religion, gender, gender identity, parental or pregnancy status, national origin, sexual orientation, age, marital status, disability, or veteran status. When we're safe, healthy, and balanced we can accomplish phenomenal things together.

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