What are the responsibilities and job description for the Director of Engineering (AI) position at KE Technology?
Lead a pioneering start up at the forefront of quantum mechanics and AI. We’re building break through novel ML models that redefine what’s possible. Backed by top-tier investors, we rank among the top 1% of Series A start ups globally, offering a rare opportunity to shape the future of AI.
We’re looking for a Director of Engineering to play a pivotal role in our next phase of growth—scaling a world-class engineering team, building high-performance infrastructure, and leading the transformation of cutting-edge research into scalable, revenue-generating ML products.
What We Offer
- Up to $350,000 base Bonus
- Equity in a rapidly growing AI start up
- Hybrid working 3 days onsite per week in NYC
Your Role
- You’ll drive the evolution from research-driven prototypes to scalable, production-ready ML systems—emphasising performance, tooling, and cross-functional execution
- Build and lead a high-performing engineering team (including HPC, ML, Infrastructure specialists)
- Define and execute the engineering roadmap in alignment with company strategy and research advancements
- Foster a culture of technical excellence, collaboration, and continuous learning
- Develop and maintain scalable, high-performance infrastructure for ML research and deployment
- Optimise distributed systems, GPU acceleration (CUDA), and parallel processing for large-scale training
- Design and implement robust ML tooling and automation pipelines.
- Support client deployment workflows, integration pipelines, and long-term infrastructure needs.
- Champion best practices in DevOps, CI/CD & infrastructure automation.
- Ensure systems are scalable, modular, well-documented, and reliable.
- Evaluate and integrate emerging technologies to improve compute efficiency and infrastructure scalability.
Requirements
- 10 years of experience, including 3–5 years in a leadership capacity
- Successfully scaled ML-first start ups from early-stage prototypes to production-grade systems
- Deep expertise in ML infrastructure, including building scalable model training and deployment pipelines.
- Proficiency in Python and C with hands-on experience using distributed computing frameworks such as Ray, Dask, Spark, and MPI.
- Practical knowledge of ML frameworks (PyTorch, TensorFlow, JAX) and MLOps tools (MLflow, Weights & Biases, Airflow, etc.)
- Strong grasp of DevOps practices, including CI/CD, orchestration and containerization (Kubernetes & Docker)
- Proven ability to lead, mentor, and grow high-performing engineering teams
- Exceptional communication and cross-functional leadership skills, with experience collaborating across research, engineering, and business units.
Bonus
- Quantum mechanics or complex linear algebra and statistics
- Expertise in high-performance computing (HPC), including CUDA, GPU programming, and parallel computing architectures
- ML applications in finance, healthcare, or chemistry
Ready to Shape the Future?
If you're excited about leading a team that's redefining the machine learning paradigm and driving impact across multiple high-stakes industries, we’d love to hear from you - apply now!
Salary : $250,000 - $350,000