CTO

Do you have experience in gRPC?, Do you have a Doctoral degree?, ML/AI Implementation & Causal AI

• 7-10 years hands-on experience building advanced ML systems in production with PyTorch or TensorFlow
• Deep expertise in causal inference methodologies and techniques., probabilistic modelling, or Bayesian methods
• Strong foundation in probabilistic graphical models and statistical inference
• Optimization algorithms: Implementing numerical optimization methods (convex, gradient-based, or meta-heuristics)
• Validation & testing: Rigorous performance measurement, benchmarking, and statistical validation frameworks
• MLOps: model versioning, training pipelines, deployment, monitoring, GPU orchestration

Complex Domain Experience (Strongly Preferred)

• Advanced forecasting systems or predictive modelling in complex operational domains (energy, finance, telecom, transportation, scientific computing)
• ML acceleration for scientific computing: physics-informed ML, GNNs, neural ODE solvers, or simulation frameworks
• Practical usage of DoWhy, CausalML, EconML, or equivalent
• Academic research or publications involving causality or probabilistic methods

Platform & Cloud Architecture

• 8+ years building production backend systems in Python (NumPy, SciPy, Pandas) + C++ and/or Rust for performance-critical components
• Data integration: Working with real-world operational data at scale (messy, streaming, high frequency)
• Deep AWS or GCP expertise: multi-region architecture, Infrastructure as Code (Terraform/Pulumi), Kubernetes
• Real-time data & streaming architecture: Designed platforms for 100k+ telemetry streams with sub-100ms latency; expertise in event-driven patterns, time-series analytics, and distributed state management
• API design: REST, WebSocket, gRPC, OAuth 2.0, mTLS

Customer-Facing Technical Skills

• Experience developing MVPs with early design partners: rapid iteration, technical co-development, customer feedback integration
• Proven ability to conduct technical sales conversations with professionals from the energy and finance sectors, as well as engineering teams and C-level executives.
• Track record building demos, POCs, and pilot architectures that convert prospects to signed customers
• Background in regulated industry (energy, finance, telco) with enterprise security/compliance requirements

IP Execution & Technical Translation

• Experience translating patent specifications, academic research, or complex technical designs into production systems
• Ability to conduct technical gap analysis between theoretical claims and practical implementation
• Track record building systems that validate novel technical approaches

Leadership & Execution

• Engineering team leadership experience
• Hands-on coder: 50%+ coding expected in Year 1
• Strong project delivery track record
• Investor-facing communication capability
• Strategic mindset for international scale-up

Required Background (One of the Following):

• Education: MSc or PhD (preferred) in Computer Science, Machine Learning, Applied Mathematics, or related field
• Experience: 8+ years software engineering, 7+ years ML engineering, 5+ years technical leadership

Language:

Mandatory: Fluency in English AND at least one of the following:

• French (native or professional proficiency)
• German (native or professional proficiency), * Have you implemented probabilistic graphical models (Bayesian networks, Markov random fields) in a production system?
• Do you have deep production experience with AWS or GCP multi-region deployments using Infrastructure-as-Code (Terraform/Pulumi)?
• How many years of work experience do you have with Python (Programming Language)?
• Are you willing to undergo a background check, in accordance with local law/regulations?
• Can you implement do-calculus or a Structural Causal Model from first principles without external resources?
• How many years of work experience do you have with Causal Inference?
• Do you have experience creating statistically rigorous benchmarking frameworks for ML model validation?
• Have you built and operated MLOps pipelines including model versioning, training, deployment, and monitoring?
• How many years of work experience do you have with PyTorch?

Education:

• Doctorate (Preferred)

• Competitive Compensation: Attractive salaries and comprehensive compensation packages that exceed industry norms (initially equity-based; exceptional salary to be activated upon funding).
• Performance Bonuses: Attractive, performance-based bonuses to acknowledge your contributions.
• Equity Ownership: Become a key stakeholder in revolutionary ventures and share in the company's success.
• Global Opportunities: Travel across Europe, GCC, Asia, and North America to make an impact on international markets and build strategic partnerships.
• Challenging Projects: Take part in stimulating projects that challenge and expand the frontiers of technology and innovation.
• Health and Wellness: Comprehensive health, dental, and vision insurance plans to support your well-being.
• Generous Paid Time Off: Enjoy flexible time-off policies that promote a healthy work-life balance, with a minimum of 25 days annually to recharge and rejuvenate.
• Research and Development Budget: Dedicated funding for attending conferences, publishing research, and ongoing learning to keep you at the forefront of your field.
• Remote Work Options: Flexibility to work remotely, with periodic in-person collaboration to enhance team cohesion.

Your mission:

• Architect and build the core platform from patent to product
• Deliver MVP and first customer proof-of-concepts
• Build and lead the founding engineering team
• Establish technical processes, standards, and engineering culture
• Lead technical strategy through seed funding and beyond
• Represent QUANTHRONEX to investors, partners, and customers