Tatari is on a mission to revolutionize TV advertising. We work with some of your favorite disruptor brands—like Calm, Fiverr, and Rocket Money—to grow their business through linear and streaming TV. We combine a sophisticated media buying platform with proprietary analytics to turn TV advertising into an automated, digital-like experience.

Named one of the Hottest Ad Tech Companies by Business Insider, and Best Places to Work by Inc. Magazine for the third consecutive year, our team includes founders and leaders from Google, Microsoft, Stripe, Shazam and Facebook. We are growing rapidly as we accelerate our mission to automate the complex landscape of managing and measuring television advertising. We have a long-term goal to make marketing on TV available to businesses of any size.

As a Senior AI Engineer, you will play a pivotal role in designing, developing, and implementing cutting-edge generative AI models and systems. Leveraging your expertise in machine learning, deep learning, and generative algorithms, you will contribute to the advancement of our organization's AI capabilities. This role demands a deep understanding of both theoretical concepts and practical applications, as well as the ability to provide technical leadership in the development of such solutions.

Responsibilities:

  • Algorithm Development: Design and implement state-of-the-art generative AI algorithms, such as 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.

Qualifications:

  • 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.

Benefits:

  • Competitive salary ($175,000 - $210,000 annually)
  • Equity compensation
  • 100% health insurance premium coverage for you and your dependents
  • Unlimited PTO and sick days
  • Snacks, drinks, and catered lunches at the office
  • Team building events 
  • $1000 annual continued education benefit
  • $500 WFH reimbursement
  • $125 pre-tax monthly stipend to spend on whatever you want
  • Annual mental health awareness app reimbursement
  • FSA and commuter benefits
  • Monthly Company Wellness Day Off (During WFH)
  • Hybrid RTO: 2 flex days a week in 2024. Likely increasing to 3 after, but no more than that. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

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Salary

$175,000 - $210,000

Yearly based

Location

New York, United States

Job Overview
Job Posted:
4 months ago
Job Expires:
Job Type
Full Time

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