Staff Software Engineer – AI/ML, MLOps

Role Overview

• Lead the design, planning, estimation, and coordination of AI/ML initiatives across multiple releases.
• Take ownership of the entire lifecycle of AI/ML systems, from experimentation to production.
• Partner with Product and Engineering teams to integrate AI/ML capabilities into company-wide projects.
• Provide strategic technical guidance on MLOps frameworks and practices, tools, and best practices.
• Foster a collaborative environment by communicating effectively across technical and non-technical teams.
• Proactively identify challenges in AI/ML workflows and propose innovative, scalable solutions.
• Drive initiatives to improve model accuracy, scalability, and reliability while adhering to privacy, security, and compliance standards.
• Ensure comprehensive documentation of models, pipelines, algorithms, and system architecture.

Requirements

• 7+ years of experience in AI/ML engineering, including MLOps, AI infrastructure, building, deploying and maintaining machine learning models in production environments.
• 3+ years of technical leadership experience, with a track record of guiding teams through complex AI/ML projects.
• Expert proficiency in programming languages such as Python, Java or Rust, and Infrastructure-as-Code with focus on MLOps, AI infrastructure design and implementation, data engineering, pipelines automation, machine learning, models evaluation and support of live production AI systems.
• Deep understanding of AI/ML systems architecture, including experience with distributed systems and large-scale data pipelines.
• Strong expertise in deploying and managing AI/ML models in cloud environments, with hands-on experience using AWS services such as Amazon Bedrock, SageMaker, and related tools, or alternatives in GCP (Vertex AI) or Azure (AI Studio) cloud.
• In-depth knowledge of model serving infrastructure, machine learning algorithms and frameworks, including experience with LLMs, AI agentic patterns, and fine-tuning pre-trained models.
• Experience with microservices architecture and CI/CD pipelines / MLOps for AI/ML model deployment, ensuring scalability, reusability, and testability.
• Experience with agentic AI coding and orchestration tools for software engineering, such as Claude Code, Codex, or similar.
• Proven ability to mentor and guide engineers, fostering growth and technical excellence without formal direct reporting relationships.
• Strong collaboration skills, working cross-functionally with Engineering, DevOps, and Product teams to deliver impactful AI/ML solutions.
• Experience with Agile/Scrum methodologies, effectively managing sprints and delivering iterative improvements.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.

Tech Stack

• AWS
• Azure
• Cloud
• Distributed Systems
• Google Cloud Platform
• Java
• Microservices
• Python
• Rust

Benefits

• 25 paid vacation days
• 8 bank holidays
• 5 paid sick days
• Work from home flexibility
• Paid parental leave
• Pension program
• Bike storage/shower facilities in building
• Career growth and development opportunities