Machine Learning Engineer, Lambda
Customer Enablement
$144-210k
+ Equity
Work from home on Tuesdays
4+ days a week in office
Deep learning infrastructure company
Be an early applicant
Deep learning infrastructure company
201-500 employees
Be an early applicant
$144-210k
+ Equity
Work from home on Tuesdays
4+ days a week in office
201-500 employees
Company mission
To accelerate human progress through computation.
Role
Who you are
- 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
Desirable
- 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
What the job involves
- 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
Our take
Lambda is a leading provider of deep learning GPU cloud services and computing hardware, founded to aid in providing a solution to the difficult problem of teaching machines how to see and learn.
Their customers include Apple, Intel, Microsoft, Linkedin, and Fortune 500 companies like Microsoft and Amazon Research, so it's no coincidence that Lambda GPU Cloud ranks number three on a google search for 'GPU cloud', behind only NVIDIA and Google itself.
With investments from 1517, Gradient Ventures, Bloomberg Beta, and Razer, Lambda intends on using the capital to expand its cloud and software, engineering teams. As well as looking to ramp up more investments into its GPU cloud, the company is constantly working to improve its hardware products.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
Feb 2024
$320m
SERIES C
Mar 2023
$44m
SERIES B
Total funding: $383m
Company benefits
- 100% remote team
- Healthcare, dental, vision, work-from-home Internet, and phone stipend.
- Vacation Plan: We offer flexible PTO to all team members as well as five sick days and twelve paid holidays each year.
- Paid Leave: Team members will receive financial security during some of life's more stressful moments, should they experience those. Offering paid parental leave, paid personal medical leave, and paid caregiver leave.
Company values
- Customers first: We seek to understand every aspect of what makes our customers tick. We focus on delivering amazing products to solve those problems and give our customers superpowers.
- Intellectual curiosity: We are always learning, diving deep, and going directly to the source.
- Humility: Everything goes smoother when work interactions are "low ego". Humility is important because admitting you don't know something is the first step to learning and improving.
- Speed: As a startup, speed of execution and the tightness of our feedback loops are two of the advantages we have over massive global companies.
Company HQ
Dogpatch, San Francisco, CA
Articles
Leadership
Michael Balaban
(Co-Founder)Graduating with a BS in Discrete Mathematics and Computer Science, Michael is experienced in software engineering and previously worked for Nextdoor as part of its infrastructure team.
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