Senior Full-Stack ML Engineer

• Productize ML pipelines for deep neural network compression by making training, compression, and evaluation workflows reproducible, observable, and cost-efficient
• Design and implement small, well-bounded backend services to a high security standard, primarily using Python
• Build frontends exposing pipelines and services to users
• Own deployment and operations, including containers, Kubernetes, CI/CD, observability, and security posture
• Make architectural decisions with the team and document them clearly for colleagues and coding agents
• Take machine learning from research code to secure, running products

Requirements

• Minimum 7 years of experience building and running production software, with a track record of shipping systems you designed yourself
• Genuine breadth across backends, data or ML pipelines, and infrastructure
• Solid grasp of software architecture and cloud platforms, including system boundaries, failure modes, and trade-offs
• Demonstrated experience training, fine-tuning, and running inference with PyTorch or TensorFlow
• Clear grasp of modern ML tooling and pipeline architecture
• Proven ability to evaluate trade-offs between model size, latency, memory, and accuracy
• Comfort with AI-assisted development and coding agents
• Security-first mindset covering trust boundaries, secrets, dependencies, and software supply chain
• Fluent in English
• Proven ability to thrive in agile, dynamic teams with fluid, cross-functional responsibilities
• Solid experience in Frontend and UX experience is a plus
• Hands-on experience with model compression, including quantization, pruning, distillation, sparsity, or inference-runtime optimization is a plus
• Familiarity with quantum computing concepts or curiosity about them is a plus
• Experience meeting formal security or compliance requirements in a small company is a plus
• Experience with distributed training, GPU scheduling, or ML cost optimization is a plus

Core Competencies

Demonstrates expertise in building and deploying machine learning pipelines, with a strong focus on security, observability, and cost-efficiency. Proficient in software architecture, cloud platforms, and modern ML tooling, ensuring high-quality, production-ready systems.

Highest-signal resume keywords

• Python Development
• Machine Learning Pipeline Architecture
• PyTorch or TensorFlow Experience
• Kubernetes and CI/CD
• Model Compression Techniques

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Deep Neural Network Compression
• Software Architecture
• Model Fine-Tuning
• Inference Optimization
• Quantization
• Pruning
• Distillation
• Sparsity
• Distributed Training

Soft Skills

• Agile Team Collaboration
• Cross-Functional Responsibilities

Industry Keywords

• Security Posture
• Observability
• Formal Security Requirements
• Compliance Requirements
• Quantum Computing Concepts

Tools & Technologies

• Kubernetes
• CI/CD
• Cloud Platforms
• AI-Assisted Development