Senior Solutions Architect II, AI/ML

🕒 April 10

🗽 New York – Remote

🗽 New York – Remote

💵 $150k - $186k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DigitalOcean

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

☁️ SaaS

SaaS • Cloud Computing

DigitalOcean is a cloud infrastructure provider that offers a suite of products and services for developers to build, deploy, and scale applications. Their platform provides comprehensive tutorials, reference material, and support documentation to assist users in managing resources effectively using their API and CLI tools. With features like Droplets (virtual machines), managed databases, Kubernetes, and a marketplace for third-party applications, DigitalOcean focuses on simplicity and performance. They cater to both individual developers and larger organizations looking for cloud solutions that are easy to implement and manage.

📋 Description

• Serve as a technical partner to Customer Success and Sales teams • Perform architecture reviews, proofs of concept, demos, and technical consultations • Uncover customer technical needs and demonstrate DigitalOcean's value proposition • Develop expertise in DigitalOcean's product portfolio, cloud landscape, and AI/ML platforms • Advocate for customers by providing product feedback, overcoming adoption blockers, and driving feature development • Provide personalized onboarding and resolve technical blockers throughout customers' cloud journeys • Design and review architectures for specific business use cases • Implement infrastructure management best practices to secure and optimize cloud resources • Identify cost reduction and performance improvement opportunities • Conduct customer workshops, training, and technical consultation sessions • Partner with Growth Account Managers and Customer Success Managers on retention and expansion success plans • Present product benefits, functionality, and technical solutions • Deploy and fine-tune LLMs and GenAI models; optimize GPU workloads using CUDA or TensorRT • Build scalable AI applications such as chatbots, inference services, and recommendation systems using Kubernetes and NFS • Design AI solutions, manage data pipelines, and integrate databases • Liaise with Engineering and Support to resolve escalations and growth obstacles • Drive process improvements and promote technical best practices • Contribute to internal and external documentation • Build tools to improve Premium Support customer experience and platform usability • Work independently and collaboratively with a global team

🎯 Requirements

• Proven professional experience with cloud infrastructure, AI/ML platforms, or equivalent education • Expertise in AI/ML frameworks such as TensorFlow and PyTorch • Familiarity with platforms like Hugging Face • Experience deploying and fine-tuning LLMs and GenAI models • Deep knowledge of Linux, distributed systems, Kubernetes, NFS, Object Storage, and GPU optimization techniques such as CUDA and TensorRT • Hands-on experience with vllm and quantization methods such as INT4, INT8, and FP8 • Programming/development experience building AI-powered applications • Experience in a post-sales or technical consultant role focused on AI/ML and cloud solutions • Knowledge of provisioning, deployment strategies, Terraform, Kubernetes, and Docker • Track record of developing successful technical solutions, including AI/ML use cases • Strong understanding of AI/ML data pipelines, cloud-native databases, and integration strategies • Strong communication skills for explaining technical AI/ML concepts clearly and concisely • Fluency in English • Cloud certifications are highly desirable, including AWS, GCP, Oracle, or Azure • NVIDIA certifications around GPU and AI/ML • Networking certifications such as Cisco or Juniper • Programming/scripting knowledge in Ruby, Python, Go, or Bash • Source code experience with Git • Automation experience with Terraform, Ansible, Chef, Puppet, or Saltstack • Virtualization experience with KVM or Xen • Database experience with MongoDB, MySQL, Redis, or PostgreSQL • Open-source experience with CoreOS, Docker, Kubernetes, Vagrant, or related certifications • DigitalOcean API, libraries, and services experience • Linux certifications such as RHCSA/RHCE

🏖️ Benefits

• Reimbursement for relevant conferences, training, and education • Access to LinkedIn Learning's 10,000+ courses • Employee Assistance Program • Local Employee Meetups • Flexible time off policy • Bonus eligibility based on company and individual performance • Equity compensation, including equity grants upon hire • Option to participate in the Employee Stock Purchase Program