Senior Full-Stack ML Engineer

Jobtailor; Helsinki; On-site; EUR 90,000 - 150,000; Full time

Job summary

Jobtailor in Helsinki is seeking an experienced engineer to productize ML pipelines for deep neural network compression, making training, compression, and evaluation workflows reproducible, observable, and cost-efficient. You will design and implement backend services in Python and build frontends exposing pipelines to users.

You will own deployment and operations, including containers, Kubernetes, CI/CD, observability, and security posture.

Qualifications

• Minimum 7 years of production software experience with shipping systems you designed yourself.
• 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

Responsibilities

• Productize ML pipelines for compression workflows with reproducibility and observability.
• Design backend services in Python and build frontends for pipelines.
• Own deployment and operations including containers, Kubernetes, CI/CD, observability, security.
• 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.
• Collaborate across teams in an agile environment.

Skills

Python Development

Machine Learning Pipeline Architecture

PyTorch or TensorFlow Experience

Kubernetes and CI/CD

Model Compression Techniques

Tools

Kubernetes

CI/CD

Cloud Platforms

Job description

• 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