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About FORE
We’re a fast-growing, venture-backed startup building cutting-edge AI solutions for Private Equity firms and their portfolio companies across Technology, Media, Fashion, and Sports. Our team moves fast, collaborates closely, and thrives on solving tough problems with real impact.
What sets us apart isn’t just the tech we build—it’s how we build it. We work with the latest advancements in AI and LLMs, but more importantly, we have the experience and drive to turn them into real, production-ready solutions. We trust each other, move fast, and take ownership, creating an environment where problem-solvers can thrive, grow, and make an immediate impact. We’ve doubled in size over the past year and are just getting started—now’s the time to join us and help shape what’s next.
The Role
We are seeking a ML Engineer with experience working with synchronized multi-camera systems and training models for action recognition.
If you're excited about tackling data-heavy challenges with a flexible mindset, we’d love to hear from you.
Responsibilities
- Design and develop machine learning models to recognize and classify movements using raw video or 3D skeletal data from multi-camera systems
- Implement pipelines for creating training and evaluation datasets
- Extract relevant features from skeletal sequences such as joint angles and trajectories
- Evaluate and benchmark hardware camera systems for performance and integration potential
- Configure camera synchronization, calibration, and 3D reconstruction pipelines
- Collaborate with internal teams to define requirements for data accuracy, latency, and usability
Required Qualifications
- Experience training models using RNNs (e.g., LSTM/GRU), CNNs, Graph Neural Networks (e.g., ST-GCN), or Transformer-based architectures for time-series or spatial-temporal data
- Familiarity with human pose estimation, motion analysis, or action recognition.
- Experience with deep learning frameworks such as PyTorch or TensorFlow
- Knowledge of data preprocessing techniques: normalization, smoothing, augmentation, time alignment.
- Familiarity with model evaluation metrics relevant to movement classification (e.g., accuracy, F1-score, temporal consistency)
Bonus Qualifications
- Experience calibrating multiple cameras to map to the same 3D coordinate system
- Familiarity with open-source pose estimation libraries (e.g., OpenPose, MMPose, MediaPipe, Anipose)
- Academic publications regarding action recognition
Location, Compensation & Benefits
Location: We are hiring for fully remote work with quarterly on-sites in Los Angeles (travel provided).
Compensation: $75k - $135k, depending on experience.
Equity: Opportunity for company equity.
Benefits
401(k) with employer match
Health insurance
Why Join Us?
- Level Up Your Skills: Work alongside top AI and NLP talent, including researchers from Stanford and Wharton, and tackle some of the most challenging problems in the field.
- Make an Impact: Take ownership of high-impact projects that solve complex, real-world problems—your work won’t sit on a shelf.
- Impactful Work: Get hands-on experience with diverse, high-impact projects.
- Flexible Environment: A small, adaptable team that values problem-solving and autonomy.
If you're passionate about ML engineering and want to work on technically engaging projects, apply now!
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