DevOps

Axomic•London, CA

2d•Remote

About The Position

Embark on an exciting journey as a Staff Software Engineer - AI/ML at OpenAsset, where you’ll play a pivotal role in shaping the future of AI/ML within our organization, and AI-enabled products we’re building to support the AEC industry. In this hands-on technical role, you’ll not only drive the development of innovative machine learning models and AI-driven solutions, leveraging frontier LLM models, agentic AI frameworks, model serving infrastructure, MLOps, LLMOps and AgentOps, agentic coding orchestration tools such as Claude Code, platforms including AWS, Amazon Bedrock, and Google GCP Vertex AI, but also strengthen the AI/ML competency at OpenAsset. You’ll help establish the team’s strategic vision, processes, and best practices. You’ll design and implement scalable, efficient, and maintainable AI/ML systems while setting the standard for excellence in model deployment, data pipeline optimization, and agentic AI applications. Beyond writing exceptional code, your leadership will be key in building a high-performing team, mentoring engineers, and tackling complex technical challenges. If you’re passionate about AI and how to build AI-based products for customers, building products from the ground up, and delivering impactful solutions, we invite you to take on this foundational role. Join us to make a lasting impact on our products, our people, and the future of AI/ML at OpenAsset.

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.

Responsibilities

Lead the design, planning, estimation, and coordination of AI/ML initiatives across multiple releases, including information extraction, model development, model serving, model training, data pipelines, and deployment.
Take ownership of the entire lifecycle of AI/ML systems, from experimentation to production, ensuring timely and high-quality delivery.
Partner with Product and Engineering teams to integrate AI/ML capabilities into company-wide projects, addressing cross-functional challenges.
Collaborate with Product, Engineering, DevOps, and other teams to ensure seamless data flow, model deployment, and system integration.
Provide strategic technical guidance on MLOps frameworks and practices, tools, and best practices that align with the company’s goals.
Research and propose advanced machine learning techniques and cloud-native AI services, including LLMs, MLOps and DevOps platforms, training and evals frameworks, and Amazon Bedrock, to enhance our capabilities.
Foster a collaborative environment by communicating effectively across technical and non-technical teams.
Mentor and guide team members through agentic coding practices, code reviews, technical coaching, and knowledge sharing, building a culture of continuous learning.
Proactively identify challenges in AI/ML workflows and propose innovative, scalable solutions.
Define and refine methods and procedures to optimize model performance, system efficiency, and team productivity.
Drive initiatives to improve model accuracy, scalability, and reliability while adhering to privacy, security, and compliance standards.
Take a leading role in addressing issues related to data quality, bias mitigation, and model interpretability with minimal oversight.
Ensure comprehensive documentation of models, pipelines, algorithms, and system architecture to support team-wide knowledge sharing.
Maintain and enhance AI/ML playbooks and best practices to streamline onboarding and continuous improvement.