Cloud Inference Engineer

Job Summary

As a Cloud Inference Engineer at a cutting-edge AI-powered company youll be the mastermind behind the scenes optimizing cloud-based systems to deliver lightning-fast scalable AI model inference. You will create install and maintain infrastructure that enables real-time predictions for applications such as recommendation engines picture recognition and natural language processing. If you enjoy combining cloud technology and AI magic this is your dream jobhelping us push the limits of what is possible while maintaining dependability and efficiency. Were looking for passionate problem solvers that thrive in a collaborative fast-paced workplace. Candidates from the United States exclusively please!

Key Responsibilities

- Design and build cloud-based inference pipelines to deploy machine learning models at scale leveraging platforms such as AWS SageMaker Google Cloud AI and Azure ML.

- Improve model serving for low-latency high-throughput inference via auto-scaling load balancing and cost management.

- Work with data scientists and software engineers to integrate models into production settings resulting in seamless CI/CD workflows.

- Monitor and troubleshoot inference systems with technologies such as Prometheus Grafana or cloud-native monitoring to ensure uptime and performance.

- Implement security best practices like as encryption access controls and GDPR/HIPAA compliance.

- Perform performance tweaking and A/B testing to increase inference speed and accuracy.

- Stay ahead of future cloud and AI technologies by contributing to research and development for next-generation inference solutions.

- Document processes and teach junior team members on cloud inference best practices.

Skills

- Proficiency in cloud platforms (AWS GCP Azure); containerization experience (Docker Kubernetes); Python Go or Java programming; familiarity with ML frameworks such as TensorFlow PyTorch or ONNX; and knowledge of serverless architectures and edge computing.

- Demonstrates strong problem-solving talents great communication skills for cross-team collaboration and the ability to simplify complex technology.

- Proficiency with DevOps tools (Terraform Ansible) and version control (Git). Capable of working independently but also contributing to a team.

Education & Experience

- A bachelors or masters degree in computer science engineering data science or a similar discipline (or comparable experience).

- 2-5 years of hands-on expertise in cloud engineering with at least 2 years dedicated to AI/ML inference or deployment.

- Demonstrated track experience of developing scalable systems; certifications such as AWS Certified Machine Learning Specialty or Google Cloud Professional ML Engineer are highly desirable.

- USA work permit is necessary; no sponsorship is offered.

Annual Pay

Competitive base income between $140000 and $180000 per year depending on experience location (cost-of-living adjustments apply) and qualifications.

Compensation & Benefits

- Benefits include ownership options annual bonuses and up to 6% 401(k) match.

- Full medical dental and vision care; HSA/FSA options; mental health support; gym reimbursements; and unlimited PTO (yes take that vacation!).

- Tuition reimbursement conference stipends and devoted time to studying new technologies.

- Flexible hours remote work setup allowance parental leave and enjoyable team events (virtual or in person).

- Company laptop home office stipend and staff discounts on technological devices.

We are an equal opportunity workplace dedicated to diversity and inclusion. If this seems like your next adventure apply now and lets create the future together!