Data Scientist at AI Sqaured

Washington, District of Columbia, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, SoftwareIndustries

Requirements

Candidates should have 5+ years of experience as a Data Scientist or Machine Learning Engineer with a proven track record of deploying models to production. A strong background in applied machine learning, Python, and ML frameworks like PyTorch or TensorFlow is required. Hands-on experience with large language models (LLMs), including fine-tuning, is strongly preferred. Proficiency in containerization and orchestration technologies such as Docker and Kubernetes, along with experience in cloud platforms (Databricks, AWS, GCP, Azure), is necessary. Familiarity with MLOps best practices, strong analytical and problem-solving skills, and excellent communication and collaboration abilities are also essential. A proactive, self-starter mindset with a passion for applied research and innovation is expected.

Responsibilities

The Data Scientist will leverage their experience to design, implement, and optimize machine learning models and pipelines. They will develop, fine-tune, and evaluate large language models (LLMs) for various applications, and collaborate with engineering and product teams to integrate AI/ML solutions into the platform. Responsibilities include conducting applied research, building end-to-end workflows from data exploration to production monitoring, and applying containerization and orchestration techniques for reproducible experimentation and deployment. The role also involves working with cloud platforms to manage data pipelines and large-scale training jobs, and ensuring AI capabilities align with platform goals and business needs.

Skills

Machine Learning

Data Science

Large Language Models (LLMs)

Python

PyTorch

TensorFlow

Model Deployment

Data Exploration

Feature Engineering

Containerization

Kubernetes

Cloud Platforms (Databricks, AWS, GCP, Azure)

Data Pipelines

Distributed Systems

AI Sqaured

Integrates AI models into business applications

About AI Sqaured

Squared.ai focuses on predictive and generative artificial intelligence to enhance business productivity. The company helps businesses integrate AI and machine learning models into their operations, making AI-generated insights more accessible. By bridging the gap between data science and business teams, Squared.ai enables faster launches of AI projects and optimizes machine learning models for real-time integration with business applications. Their services include designing user-friendly experiences and ensuring model performance through real-time monitoring and auto-tuning. This approach allows businesses to gain insights quickly without lengthy development cycles. The goal of Squared.ai is to democratize AI, making it easier for organizations to adopt and leverage AI-driven decision-making.

Washington, District of ColumbiaHeadquarters

2021Year Founded

$19.3MTotal Funding

SERIES_ACompany Stage

Data & Analytics, AI & Machine LearningIndustries

51-200Employees

Risks

Emerging competition from Nvidia's mini supercomputer offering significant AI computing power.

Integration challenges from Multiwoven acquisition may disrupt operations.

Rapid expansion post-funding could lead to overextension and resource strain.

Differentiation

AI Squared bridges data science and business teams for faster AI project launches.

The platform democratizes AI-enhanced decision-making for businesses.

Real-time performance monitoring ensures optimal AI model performance in business applications.

Upsides

Acquisition of Multiwoven enhances data integration capabilities for seamless AI model integration.

Partnership with UNIFI Music expands AI integration services into the music industry.

$13.8M Series A funding boosts AI integration capabilities and platform features.

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