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Full-Time

Generative AI Scientist

Confirmed live in the last 24 hours

Mission Cloud

Mission Cloud

201-500 employees

AWS Premier Tier Services and Cloud Managed Provider

Consulting
Hardware
Energy

Compensation Overview

$176k - $198kAnnually

Mid, Senior, Expert

Remote in USA

Category
Applied Machine Learning
AI & Machine Learning
Required Skills
Python
Tensorflow
Data Structures & Algorithms
Pytorch
AWS
Natural Language Processing (NLP)
Computer Vision
Requirements
  • Proven experience in implementing and deploying generative AI models in practical applications
  • Strong programming skills in languages like Python, TensorFlow, PyTorch, or similar AI frameworks
  • Solid understanding of deep learning architectures and generative models such as GANs, VAEs, etc
  • Familiarity with natural language processing (NLP) and computer vision (CV) applications in generative AI
  • Experience in data pre-processing, feature engineering, and data augmentation for training generative models
  • Proficiency in data manipulation, statistical analysis, and model evaluation techniques
  • Strong problem-solving and analytical skills, with the ability to think creatively and adapt to new challenges
  • Excellent communication skills to collaborate with interdisciplinary teams and present complex technical concepts to non-technical stakeholders
  • Passion for continuous learning and a keen interest in exploring the potential of generative AI in various industries
  • AWS Solution Architect - Professional Certification (required within 6 months of hire)
  • AWS Specialty Certification - Machine Learning (required within 1 year of hire)
Responsibilities
  • Facilitate design sessions with the Mission Cloud team to create the strategy, architecture, and implementation plan for generative AI implementation
  • Design, develop, and deploy generative AI models that demonstrate high performance and efficiency in solving complex problems
  • Collaborate with data scientists, engineers, and domain experts to integrate generative AI solutions into existing systems or products
  • Implement and fine-tune existing generative AI algorithms and models to meet specific use-case requirements, including scalability and resource efficiency
  • Conduct thorough testing and validation of generative AI solutions to ensure accuracy, reliability, and robustness
  • Communicate proposed solutions to internal team so they understand the benefits, translating technical elements into business language
  • Develop strategic roadmaps and project plans based on Mission goals
  • Work with Project Managers to set customer expectations, drive alignment, and coordinate timelines
  • Explore and experiment with the latest advancements in generative AI research to improve system performance and capabilities
  • Stay up-to-date with the latest trends, tools, and technologies in the generative AI field
  • Document the implementation process, provide technical documentation, and contribute to knowledge sharing within the team
  • Lead strategic initiatives within Mission Cloud to keep DAML at the forefront of AI and AWS technologies
  • Contribute marketing materials for Mission Cloud in the Generative AI space

Mission Cloud is a leading AWS Premier Tier Services Partner and Cloud Managed Services Provider, offering agile cloud services to help businesses migrate, manage, modernize, and optimize their AWS environments. Their Mission Control platform provides real-time visibility into cloud performance and is supported by expert CloudOps, FinOps, and InfraOps teams, empowering companies to capitalize on cost and performance opportunities and accelerate their growth.

Company Stage

Series B

Total Funding

$40M

Headquarters

El Segundo, California

Founded

2017

Growth & Insights
Headcount

6 month growth

-5%

1 year growth

-4%

2 year growth

-1%

Benefits

Medical, dental, and vision insurance

401(k) plan with company matching

Profit sharing bonuses based on performance

Flexible Spending Accounts (Health and Dependent Care)

Paid time off

Inclusive work environment with several Employee Resource Groups

Flexible work hours

Home office expense benefit

Cell phone stipend

Flex stipend