Offer summary

Qualifications:

Experience in machine learning or data science, Familiarity with deep learning frameworks, Knowledge of containerization technologies like Docker and Kubernetes, Experience in building end-to-end ML pipelines, Linux systems administration experience.

Key responsabilities:

Guide customers through technical onboarding and workload migration

Collaborate to understand customer needs and provide best practices

Create documentation, architecture diagrams, and conduct training sessions

Identify opportunities to enhance product adoption and customer growth

Serve as a link between customers and internal teams

Job description

In 2012, Lambda started with a crew of AI engineers publishing research at top machine-learning conferences. We began as an AI company built by AI engineers. That hasn't changed. Today, we're on a mission to be the world's top AI computing platform. We equip engineers with the tools to deploy AI that is fast, secure, affordable, and built to scale. Whether they need powerhouse GPU hardware on-site or the flexibility of cloud-based solutions, we've got the horsepower to make it happen. Lambda’s AI Cloud has been adopted by the world’s leading companies and research institutions including Anyscale, Rakuten, The AI Institute, and multiple enterprises with over a trillion dollars of market capitalization. Our goal is to make computation as effortless and ubiquitous as electricity.

If you'd like to build the world's best deep learning cloud, join us.

*Note: This position requires presence in our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

What You’ll Do

Guide new customers through the technical onboarding process by:

Assisting ML researchers in migrating their existing workloads to Lambda’s AI Cloud Platform, ensuring that expected performance is achieved
Providing initial troubleshooting for technical issues that arise during the first few days of customers time on Lambda infrastructure

Collaborate closely with customers to understand their needs and objectives, offer tailored guidance and best practices for deploying models and managing GPU infrastructure
Demonstrate how to optimize and scale training and inference workloads within Lambda by:

Building proof-of-concept demos
Creating detailed architecture diagrams

Create and maintain detailed documentation including technical guides, best practices and troubleshooting resources
Conduct training sessions and workshops for customers, enabling them to effectively utilize Lambda’s products and services
Facilitate smooth workload transitions between Lambda’s various products
Drive customer growth by identifying opportunities to increase product adoption
Act as a trusted advisor to new customers, ensuring successful integration and optimization of Lambda products
Provide continuous customer feedback to influence product roadmap and enhancements
Serve as a link between customers and internal teams

You

Have experience in machine learning or data science with a deep understanding of model development, and deployment
Have experience using deep learning frameworks and libraries such as PyTorch, Tensorflow, Deepspeed, etc.
Have experience with containerization technologies such as Docker and Kubernetes
Have experience building and optimizing LLM-based applications
Have experience building end-end ML pipelines on major cloud platforms
Have experience with Linux systems administration
Are an excellent communicator, capable of explaining complex, technical concepts to technical and non-technical audiences
Are customer obsessed, and strive to deliver exceptional experiences to current and future Lambda customers
Experience as an ML educator and/or building and executing customer training sessions, product demos or workshops

Nice to Have

Experience using MLOps tools such as RunAI, Weights and Biases, ClearML
Experience in training large models using distributed systems

Selecting parallelism strategies
Multi-GPU and Multi-Node training
Troubleshooting and configuring NCCL/RDMA
Quantization

Experience with HPC orchestration technologies such as SLURM
Experience with automation tools like Ansible, Puppet, Salt

Salary Range Information

Based on market data and other factors, the salary range for this position is $144,000 - $210,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

We offer generous cash & equity compensation
Investors include Gradient Ventures, Google’s AI-focused venture fund
We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
We have a wildly talented team of 300, and growing fast
Health, dental, and vision coverage for you and your dependents
Commuter/Work from home stipends for select roles
401k Plan with 2% company match
Flexible Paid Time Off Plan that we all actually use

A Final Note:

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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