Staff ML Ops Engineer

Job not on LinkedIn

🕒 February 4

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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Albert Invent

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🤖 Artificial Intelligence

🧬 Biotechnology

🔬 Science

💰 Seed Round on 2023-06

Artificial Intelligence • Biotechnology • Science

Albert Invent is an end-to-end platform that digitalizes synthesis, formulation, and materials science for the age of AI. It combines capabilities like inventory management, Electronic Lab Notebooks (ELN), Lab Information Management Systems (LIMS), and regulatory intelligence to streamline research and development processes. Trusted by thousands of chemists across 36 countries, Albert Invent enhances productivity and accelerates innovation in chemical research through the use of advanced AI and machine learning technologies.

📋 Description

• Design, deploy, and maintain Kubernetes infrastructure supporting AI/ML workloads • Manage containerized services, autoscaling, networking, and resource optimization • Design and build high-performance Python APIs and services using FastAPI or similar frameworks • Architect backend systems for scalability, reliability, and low latency • Build integrations between AI/ML systems and the broader Albert platform • Build and operate distributed systems that handle compute-intensive and high-throughput workloads • Design for fault tolerance, graceful degradation, and horizontal scalability • Implement async workflows, job queues, and task orchestration as needed • Architect and maintain data pipelines and storage systems supporting AI/ML workflows • Implement observability including logging, metrics, tracing, and alerting • Own system reliability—troubleshoot issues, conduct post-mortems, and continuously improve • Design CI/CD pipelines and promote automation best practices • Partner closely with ML engineers to understand requirements and deliver production-ready infrastructure • Translate ML prototypes and research code into scalable, maintainable systems

🎯 Requirements

• A degree in Computer Science or a related field with 7+ years of industry experience (Bachelor's) or 5+ years (Master's or PhD) in software engineering • Experience supporting AI/ML teams or deploying ML systems in production • Experience with GPU workloads and scheduling • Advanced proficiency in Python including async programming and performance optimization • Deep experience with Kubernetes—cluster management, networking, autoscaling, and troubleshooting • Strong background in distributed systems and microservices architecture • Experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code • Proficiency in REST API development using FastAPI, Flask, or similar • Experience with containerization and CI/CD pipelines • Track record of operating production systems at scale

🏖️ Benefits

• Health insurance • Flexible working hours • Professional development opportunities