Join a cutting-edge AI company pioneering a new era in machine learning-drawing inspiration from quantum mechanics and human cognition. This team is transforming how models learn and infer by building a proprietary Quantum Cognition Machine Learning (QCML) framework that outperforms traditional methods in real-world, high-dimensional applications across finance, genomics, robotics, and more.
This is a rare opportunity to work on technology that bridges the gap between deep research and impactful engineering. You'll contribute directly to ML experimentation, model benchmarking, and productization efforts-helping shape a next-generation AI platform that operates efficiently on classical hardware while solving some of the most complex data challenges today.
What You'll Be Doing
Tech Breakdown - 50% ML experimentation and benchmarking
- 30% Engineering and ML infrastructure development
- 20% Cross-functional collaboration with research and client teams
Daily Responsibilities - Analyze structured and unstructured datasets, perform EDA, and prepare data for experimentation
- Build baseline models (Random Forest, XGBoost, Deep Neural Nets) to evaluate performance of proprietary ML technology
- Run reproducible experiments, track performance metrics (R , F1, AUROC, etc.), and generate insights
- Improve internal ML pipelines and infrastructure to support scalable PoC delivery
- Work with researchers and client-facing teams to ensure results align with business needs and timelines
- Help shape best practices in model deployment, experiment reproducibility, and toolchain optimization
Required Skills & Experience - 4+ years of hands-on experience in machine learning
- Strong programming skills in Python and ML libraries (scikit-learn, PyTorch, JAX, or TensorFlow)
- Experience with model development, evaluation, and performance optimization
- Familiarity with ML fundamentals-classification, regression, metrics, and experimentation frameworks
- Proficient in data wrangling, version control (Git), and feature engineering
- Strong written and verbal communication skills; able to collaborate across technical and business teams
Bonus Qualifications - Background in quantum mechanics or advanced linear algebra
- Experience with time-series, biological, or chemical data
- Exposure to cloud platforms (AWS, GCP, Azure)
- Familiarity with modern ML approaches such as active learning, reinforcement learning, or generative models
- Previous experience in client-facing or consulting roles
The Offer - Competitive salary and benefits
- Remote-friendly role with the option to work onsite with a collaborative team
- Opportunity to work on a novel, paradigm-shifting ML framework
- High-impact work across industries including finance, defense, genomics, and robotics
- Significant opportunities for career growth, learning, and working closely with a world-class research and engineering team
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
Posted by: Fedro De Tomassi
Specialization : - Python
- Machine Learning/Data Science