Machine Learning Engineer Jobs in Santa Rosa, CA

Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs.

We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver and Bangalore, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale.

We are seeking an experienced DevOps Engineer to join our growing team and play a pivotal role in designing and building our platform and infrastructure as we continue to scale our product and user base. As a part of our team, you will be working in a dynamic, fast-paced environment to ensure the reliability, scalability, and performance of our systems, while focusing on service architecture and deployment, query optimization, distributed systems, data and machine learning infrastructure, and security and authentication. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact.

1. Partner with product teams to architect, design, and build the foundational infrastructure for our products.

2. Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on any one of the public cloud networks like AWS, Azure and GCP. Leverage technologies such as Kubernetes, Helm, Terraform, and Istio to achieve infrastructure resilience.

3. Drive the automation of infrastructure tasks, from provisioning to configuration management and deployment, utilizing tools like Terraform, Ansible, and Kubernetes.

4. Collaborate closely with the software development team to refine CI/CD pipelines, e.g., using GitHub Actions and Cloud Build tools, enhance service interfaces, and improve the overall developer experience.

5. Architect and implement advanced observability solutions using tools like Prometheus and Grafana. Ensure real-time alerting and error tracking with Sentry and Pagerduty to maintain system health and performance.

6. Deploy comprehensive testing frameworks, including tools like Selenium for end-to-end testing. Ensure robust integration and system testing to maintain software quality.

7. Performance Analysis: Regularly monitor system health, analyze performance metrics, and recommend enhancements. This includes optimizing database queries and ensuring peak database performance.

1. ML/OPs experience

2. Experience with Postgres query optimization and related performance improvement techniques.

3. Experience with event-driven data and machine learning infrastructure, including streaming pipelines, database systems, model training

4. Experience with air-gapped cloud environments or private clouds

5. Experience administering complex deployments on Azure, especially AKS

• Bachelor's or Master's degree in Computer Science or related field.

• 3+ years of experience in Infrastructure engineering, or a similar role,

• Excellent problem-solving skills and the ability to work under pressure in a fast-paced environment.

• Ability to work independently and as part of a team

• Experience working with global teams

For California based candidates:
The standard base salary for this position is $135,000-$225,000 annually.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.