Research Scientist Intern, AI Core Machine Learning Job at Meta (Sunnyvale)

Research Scientist Intern, AI Core Machine Learning

We are committed to advancing the field of artificial intelligence by making fun...

Location

United States , New York

Salary:

7650.00 - 12134.00 USD / Month

Lead Data Scientist

Prism is seeking a Lead Data Scientist who will make high-impact, hands-on contr...

Location

United States , NYC or San Diego (La Jolla/UTC)

Salary:

140000.00 - 160000.00 USD / Year

Prism Data

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Statistics, Data Science, Math, Industrial Engineering, or similar quantitative discipline required
4+ years of experience as a Data Scientist or Statistician, preferably in credit risk or financial services
Research & development of new attributes, models, decision strategies, and/or analytic capabilities
Customer-facing testing of data or analytic solutions (e.g., credit risk scores, alternative data, fraud prevention, etc.)
Collaboration with business teams to understand and address business problems
Modeling experience in the latest AI and machine learning approaches
Mastery of rudimentary modeling approaches (e.g., regression, decision trees)
Knowledge of data labeling/categorization, feature development and selection, model design and training, testing, coding, implementation, monitoring, and governance
Financial services industry data expertise, including types of data sources applicable to different types of business decisions based on regulatory factors
Experience evaluating alternative statistical approaches, including review of academic papers on new techniques and ideas, and justifying which approach is best suited for which problems and why

Job Responsibility

Maintain and advance existing analytical product suite
Enhance core cash flow underwriting offerings as new data elements become available
Develop next-generation versions of products to boost stability, predictive accuracy, and relevancy to emerging use cases
Develop new products for new market opportunities using novel data assets
Demonstrate best practices in transparent modeling approaches to enable easy client adoption
Support sales, revenue attainment, and thought leadership
Conduct proof of concept analyses of the efficacy of Prism products in the context of clients’ business problems, and present results and insights
Support new and existing clients by guiding them on score cutoffs and the use of powerful custom attribute sets for their business
Educate clients on technical product knowledge
Contribute analysis to thought leadership content delivered by Prism executives in white papers and industry conferences

What we offer

medical
dental
vision
401(k)
equity-based compensation

Fulltime

Computer Vision Intern

Join our AI-focused internship to gain hands-on experience developing cutting-ed...

Location

Switzerland , Basel

Salary:

Not provided

MDPI

Expiration Date

Until further notice

Requirements

Master’s degree in Data Science, Machine Learning, Artificial Intelligence, or a closely related field is required
a PhD in these areas is considered a strong advantage
Less than 2 years of professional or hands-on experience in Computer Vision, AI/Data Science, and Linux-based environments
Advanced proficiency in English, with strong written and verbal communication skills
Working knowledge of Microsoft O365 tools for documentation and collaboration
Basic proficiency in Python for building complex applications and developing machine learning models
Familiarity with technologies such as FastAPI, Celery, and Keycloak
Solid understanding of core Artificial Intelligence principles and methodologies
Hands-on exposure to deep learning frameworks such as PyTorch or TensorFlow for image analysis and model development
Experience using computer vision libraries including OpenCV, scikit-image, and Pillow for image preprocessing and feature extraction

Job Responsibility

Support the preparation of a proof-of-concept prototype capable of detecting image manipulations and its integration into the editorial workflows
Contribute to the development of an AI-driven system designed to detect various types of image and figure manipulations in academic publications
Conduct research and experimentation on computer vision and image forensics techniques, including duplication detection, splicing, retouching, and contrast or brightness alterations
Develop and evaluate machine learning and deep learning models (e.g., CNNs, autoencoders, transformers) for anomaly and similarity detection in scientific figures
Collect, preprocess and analyze image datasets extracted from academic manuscripts, ensuring data quality and representative coverage of manipulation types
Collaborate with data engineers and data scientists to design scalable training pipelines, manage large image datasets, and benchmark algorithmic performance
Explore and implement relevant open-source tools, datasets, and research methods in the field of digital image forensics
Document experimental results, model architectures, and findings, contributing to internal technical reports and presentations

What we offer

The opportunity to contribute to the academic/scientific community
Flexible working hours
Team bond strengthening through team-building events
Professional growth opportunities with our global training system
Working in a collaborative and socially responsible team
Company retreat facility
Full-coverage insurance for accidents/daily sickness
Prime location near Basel train station and city center

Fulltime

Data scientist

The Goodstuff Data Scientist is responsible for extracting, transforming and loa...

Location

United Kingdom , London

Salary:

Not provided

Goodstuff

Expiration Date

Until further notice

Requirements

Strong analytical and numerical ability
Confidence in ETL techniques encompassing multiple sources
High levels of organisation and excellent attention to detail
A confident, committed and professional approach
Self-sufficiency and the ability to prioritise workloads, with good judgement on when and how to seek wider team support
The ability to distil complex data set-ups into simple, clear routes to solutions for a range of stakeholders
Experienced in SQL and passionate about AI and its scope for development. Media experience an advantage but not essential
Passionate to be an internal advocate for data and automation
A strong team orientation and a proactive self-starter
Effective time-management and the ability to work across multiple workstreams at once

Job Responsibility

Extract, transform and load data (ETL) to support data warehousing, visualisation and automation
Use an analytical mindset to scope, design and document data to power AI and machine learning
Help to build and maintain robust data pipelines, including scheduling, monitoring refreshes, troubleshooting failures and ensuring outputs are formatted correctly to support automation, modelling and AI tools
Develop efficient, readable and structured code (e.g. SQL and other languages) to process data when briefed, with an eye on reuse, scalability and error-handling, including for AI and ML-driven workflows
Get to grips with the key tools and systems for the role – including bespoke internal platforms and R-Studio, Power BI, Looker Studio, SQL, Mediaocean, and SMI
Build a strong understanding of how media data flows from research → planning → delivery → evaluation, and how Data Science, machine learning and AI techniques can support planning, optimisation and measurement
Apply data quality best practice: running validation checks and reconciling data across sources and support the creation of clear, intuitive data visualisations and dashboards that make complex datasets easy to understand
Work with internal teams to ensure data handling is secure and compliant, escalating any risks or issues, especially in the context of AI, automation and model governance
Learn to manage data flows, working with internal and external stakeholders to ensure timely and accurate delivery of projects
Develop strong relationships with internal teams and wider network agencies to support with analysis and reporting on projects to realise our data ambitions

Applied AI/ML Scientist

As an Applied AI Scientist in the FieldML team, you will be responsible for deve...

Location

United Arab Emirates

Salary:

Not provided

Cerebras Systems

Expiration Date

Until further notice

Requirements

Master’s or PhD in Computer Science, Machine Learning, or related fields
Expert-level understanding of modern model architectures, including dense transformers, MoEs, multimodal and sequence models, scaling laws and training dynamics
Proven track record of training and/or fine-tuning large models (1B+ parameters) and direct experience with the challenges of large-scale model training
Mastery of Python and PyTorch, experience with distributed training frameworks and large-scale distributed data processing pipelines and tools
Strong interpersonal and communication skills
Effective in collaborative and fast-paced team settings, able to work autonomously and within a team in a dynamic environment, managing multiple projects and pivoting as customer needs evolve

Job Responsibility

Customer Use Case Discovery & Project Scoping
Collaborate with customer stakeholders to identify the best approaches to their business problem with AI
Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures
Define project milestones, success metrics, and rigorous evaluation benchmarks
Custom SOTA Models and AI Systems Development
Architect and execute end-to-end training recipes for custom models, tailoring model architecture and training recipes to meet customer-specific performance and accuracy requirements
Design and implement sophisticated adaptation strategies, including continuous pre-training on private datasets, supervised fine-tuning (SFT), and post-training alignment via RLHF or DPO
Take full ownership of the training pipeline, from high-performance data preprocessing and tokenization to hyperparameter tuning and loss-curve analysis
Navigate the nuances of model convergence on specialized hardware
Scale training workloads across Cerebras clusters

What we offer

Build a breakthrough AI platform beyond the constraints of the GPU
Publish and open source their cutting-edge AI research
Work on one of the fastest AI supercomputers in the world
Enjoy job stability with startup vitality
Our simple, non-corporate work culture that respects individual beliefs

Senior Data Scientist

We are looking for a hands-on Senior Data Engineer / Data Scientist to design an...

Location

United States

Salary:

110720.00 - 138400.00 USD / Year

Bugcrowd

Expiration Date

Until further notice

Requirements

5+ years of experience in Data Science, Machine Learning Engineering, or Data Engineering
Deep experience with Python, AWS services (S3, Lambda, Batch, Glue, Bedrock, Step Functions, Redshift), and ML frameworks (Scikit-Learn, XGBoost, PyTorch, etc.)
Proven experience building end-to-end ML pipelines — from data ingestion to model deployment and monitoring
Strong understanding of LLM technologies, RAG architectures, and API integration with AI systems
Ability to design and manage data architectures for large-scale, multi-tenant environments
Experience applying ML or automation to security or operational intelligence domains
A builder’s mindset — passionate about shipping scalable, practical AI systems

Job Responsibility

Design, develop, and deploy LLM- and RAG-powered applications that enhance analyst and hacker productivity across offensive security use cases
Integrate Generative AI models (e.g., via AWS Bedrock, OpenAI, Anthropic) with internal APIs and security datasets to automate and augment workflows
Build and fine-tune ML models for vulnerability prediction, triage prioritization, and exploit pattern detection
Develop evaluation pipelines and feedback loops to continuously improve AI model performance and explainability
Architect and maintain large-scale, high-performance data pipelines to process vulnerability, asset, and activity datasets from multiple sources
Build secure data ingestion, transformation, and storage workflows leveraging AWS (Glue, Lambda, Step Functions, S3, Redshift, Bedrock) and modern MLOps practices
Develop robust CI/CD pipelines for data and ML model deployment using AWS CDK and testing frameworks
Partner with infrastructure teams to scale AI workloads efficiently and securely across multi-tenant environments (FedRAMP, SOC2)
Collaborate with security researchers and engineers to translate offensive security workflows into data-driven automation
Integrate ML and AI systems with core security platforms such as the MCP server, Bugcrowd Connect, and vulnerability intelligence pipelines

Fulltime