Senior AI Engineer
Updated on 3/21/2024
Tatari

201-500 employees

Linear & streaming TV data analytics
Company Overview
Tatari’s mission is to provide the knowledge and transparency needed to give a competitive edge, and to create a clear way forward for advertisers everywhere. The company combines a sophisticated media buying platform with proprietary analytics to turn TV advertising into an automated, digital-like experience.
Data & Analytics

Company Stage

N/A

Total Funding

N/A

Founded

2016

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

-4%

1 year growth

-4%

2 year growth

-3%
Locations
New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Tensorflow
Data Structures & Algorithms
Pytorch
CategoriesNew
AI & Machine Learning
Applied Machine Learning
Deep Learning
AI Research
Requirements
  • Proven track record of at least 5 years in the field of machine learning or related areas.
  • Proven track record of at least 2 years in the field of generative AI or related areas
  • Proficiency in deep learning frameworks such as TensorFlow, PyTorch or similar.
  • Expertise in generative models, neural networks, and reinforcement learning.
  • Deep experience or advanced degree (Ph.D. or equivalent) in Computer Science, Machine Learning, or a related field.
  • Demonstrated ability to lead and mentor a team of AI engineers.
  • Strong communication skills to convey complex concepts to both technical and non-technical stakeholders.
  • Analytical mindset with the ability to tackle complex problems and provide innovative solutions.
  • Ability to adapt to evolving technologies and methodologies in the rapidly changing field of AI.
Responsibilities
  • Algorithm Development: Design and implement state-of-the-art generative AI algorithms, such as GANs, VAEs, Transformers, and other deep generative models, to empower media buying decisions.
  • Algorithm Development: Design and implement large recommender systems based on GNN embeddings and similar methodologies, to empower media buying decisions.
  • Optimize and fine-tune existing algorithms to enhance performance, scalability, and efficiency.
  • Lead the training and evaluation of generative models on large-scale datasets.
  • Develop methodologies for assessing model performance and making improvements based on feedback.
  • Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate generative AI into various applications.
  • Provide guidance and mentorship to junior team members.