Machine Learning Operations (MLOPs) Architect - GCP - (US Remote)

What you will be doing:

• Architect and optimize our existing data infrastructure to support cutting-edge machine learning and deep learning models.
• Collaborate closely with cross-functional teams to translate business objectives into robust engineering solutions.
• Own the end-to-end development and operation of high-performance, cost-effective inference systems for a diverse range of models, including state-of-the-art LLMs.
• Provide technical leadership and mentorship to foster a high-performing engineering team.
• Develop CI/CD workflows for ML models and data pipelines using tools like Cloud Build, GitHub Actions, or Jenkins.
• Automate model training, validation, and deployment across development, staging, and production environments.
• Monitor and maintain ML models in production using Vertex AI Model Monitoring, logging (Cloud Logging), and performance metrics.
• Ensure reproducibility and traceability of experiments using ML metadata tracking tools like Vertex AI Experiments or MLflow.
• Manage model versioning and rollbacks using Vertex AI Model Registry or custom model management solutions.
• Collaborate with data scientists and software engineers to translate model requirements into robust and scalable ML systems.
• Optimize model inference infrastructure for latency, throughput, and cost efficiency using GCP services such as Cloud Run, Kubernetes Engine (GKE), or custom serving frameworks.
• Implement data and model governance policies, including auditability, security, and access control using IAM and Cloud DLP.
• Stay current with evolving GCP MLOps practices, tools, and frameworks to continuously improve system reliability and automation.

Requirements:

• Proven track record in designing and implementing cost-effective and scalable ML inference systems. 
• Hands-on experience with leading deep learning frameworks such as TensorFlow, Pytorch, HuggingFace, Langchain, etc. 
• Solid foundation in machine learning algorithms, natural language processing, and statistical modeling. 
• Strong grasp of fundamental computer science concepts including algorithms, distributed systems, data structures, and database management. 
• Ability to tackle complex challenges and devise effective solutions. Use critical thinking to approach problems from various angles and propose innovative solutions.
• Worked effectively in a remote setting, maintaining strong written and verbal communication skills. Collaborate with team members and stakeholders, ensuring clear understanding of technical requirements and project goals.
• Expertise in public cloud services, particularly in GCP and Vertex AI.

Must have:

• Proven experience in building and scaling Agentic AI systems in a production environment.
• In-depth understanding of LLM architectures, parameter scaling, and deployment trade-offs.
• Technical degree: Bachelor's degree in Computer Science with a minimum of 10+ years of relevant industry experience, or
• A Master's degree in Computer Science with at least 8+ years of relevant industry experience.
• A specialization in Machine Learning is preferred. 

Travel

• Travel as needed per business requirements

Sponsorship

• This role is not sponsorship eligible
• Candidates need to be legally able to work in the US for any employers