Machine Learning Researcher

What You’ll Do

• You will work on developing and refining AI models. Publishing research outcomes in the form of dataset, model, demo apps and publications..
• You will also collaborate with colleagues across the organization to benchmark and optimize ML workloads on our GPU platforms.
• The ideal candidate will possess a solid research background with experience in generative models.

You 

• Demonstrate a proven track record of enhancing existing machine learning methodologies, evidenced by significant achievements such as first author publications or notable projects.
• Manage and advance a research agenda, including selecting meaningful research problems and independently conducting long-term projects.
• Execute model training at scale, either by managing multiple experiments concurrently or overseeing critical high-cost runs to ensure optimal performance.

Nice to Have

• Experience in MLOps within a collaborative environment.
• Experience in training large models using distributed systems.
• Experience in creating high-performance implementations of deep learning algorithms.

Salary Range Information 

Based on market data and other factors, the salary range for this position is $189,000 – $260,000. 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