AI Jobs

Benefits:

• Health Care Coverage

• Education Reimbursement

• Competitive Paid Time Off

• 4 Self-Care Days per year

• Parental Leave

Education Requirements:

• Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field

Experience Requirements:

• Software engineering background with at least 8 years of experience

Other Requirements:

• Proficiency in Python, SQL, Unix-based systems, git, and github

• Machine / Deep Learning development skills

• Fluent in written and spoken English

Responsibilities:

• Work with subject matter experts to determine product questions

• Curate, generate, and annotate data and create optimal datasets

• Develop and tune Machine Learning models

• Utilize, adopt, and fine-tune Language Models

• Optimize models for scaled production usage

Benefits:

• Base salary + equity + performance bonus

• Industry-leading healthcare covering medical, dental, vision, and life paid by the company

• Health Savings and Flexible Spending accounts

• 401K

• Unlimited PTO with an employee-focused work approach

Education Requirements:

• Academic background in statistics, comp sci, math, engineering

Experience Requirements:

• 6+ years professional Data Science experience

• Deep ML/AI experience (including machine learning modeling and ensemble methodology)

• Python expertise (NumPy, SciPy), SQL, MongoDB, C++

Other Requirements:

• Consumer product and subscription modeling expertise

• Understanding of digital signal processing techniques (filtering, spectral/FFT analysis, convolution, etc.)

• Experience with machine learning, especially as it applies to music analysis and/or generation

• Familiarity with python audio processing libraries such as Librosa

• Passion for or experience in music – ML, production, and creation

Responsibilities:

• Collect, analyze, and present processed and unprocessed data pertaining to music creation tech

• Design accurate and scalable prediction algorithms in pertinence to business objectives

• Collaborate with the engineering team to bring analytical prototypes to production

• Make clear recommendations to improve and work with other department leads to execute

• Help design data team hiring roadmaps

Benefits:

• Top-notch health coverage for you & your family

• Generous 401(K) contribution

• Up to 20 weeks paid leave for new parents

• 4 weeks of PTO

• Daily in-office catering plus a monthly Doordash stipend

Experience Requirements:

• 7+ years of experience as a Data Scientist working on consumer-facing products

• Direct experience supporting monetization systems (subscriptions, ads, or virtual currencies)

• Experience building or scaling data science practices

Other Requirements:

• Strong intuition for identifying high-impact insights

• Proven ability to turn analysis into product decisions

• Comfortable working in experimental environments with incomplete data

Responsibilities:

• Partner with product and engineering teams to drive data-informed monetization

• Define success metrics and lead experimentation

• Translate complex behavioral and economic data into actionable insights

• Build data science foundations to support rapid product iteration

Benefits:

• Top-notch health coverage for you & your family

• Generous 401(K) contribution

• Up to 20 weeks paid leave for new parents

• 4 weeks of PTO

• Daily in-office catering plus a monthly Doordash stipend

Experience Requirements:

• 7+ years of experience in data science leadership at chat, social media, or UGC product companies

• 2+ years of experience as a data scientist supporting the trust & safety function

Other Requirements:

• Strong intuition for choosing the right questions and driving to key insights

• Ability to stand up data science tools and systems

• Experience with ecosystems data science or B2C/C2C marketplaces

Responsibilities:

• Support the Safety team across product areas

• Focus on the two-sided ecosystem of Creators and Users

• Design innovative, user-centered solutions

• Collaborate closely with cross-functional product teams

• Turn findings into actionable next steps and execute with engineering

Benefits:

• Competitive salary

• Equity (own a piece of the company)

• True ownership & flexibility

• Minimal bureaucracy

• AI-first culture

Education Requirements:

• Strong math skills (linear algebra and statistics)

Experience Requirements:

• Experienced Data Scientist / ML Engineer

• Foundational knowledge of NLP and LLMs

• Experience with Python, NumPy, PyTorch, Hugging Face, Flyte, or PySpark

• Past experience with entity resolution, information extraction, or document retrieval

Other Requirements:

• Startup-minded and high-performer

• Hunger for innovation

• Knowledge of how to make ML pipelines and products scale

• Fluency in English

Responsibilities:

• Work on complex, data-heavy features

• Define what a great AI-first product looks like

• Address entity resolution and information extraction

• Manage document retrieval, ranking and clustering

Education Requirements:

• PhD (or near completion) in a relevant field or equivalent experience

Experience Requirements:

• experience applying image/video generation models

• foundations in generative modeling

• deep familiarity with diffusion models

• understanding of video-language models and multimodal generation

• proficiency in PyTorch and GPU-based inference

Other Requirements:

• experience with long-video or audio generation

• skills in 3D graphics or Gaussian splatting

• publications in top-tier venues (CVPR, NeurIPS, etc.)

• familiarity with software engineering best practices

Responsibilities:

• research and develop audio-visual generation models

• focus on models coupled with conversation flow

• experiment with diffusion models and long-video generation

• collaborate with Applied ML team for production implementation

• stay ahead of latest advancements in multimodal generation

Experience Requirements:

• 5+ years of hands-on experience in AI, Machine Learning, and Data Science

• Expertise in LLMs, including fine-tuning, distributed training, quantization, and pruning

• Experience working with OCR, ASR, and TTS applications in real-world deployments

• Proven experience deploying AI models in production at scale

• Proficiency in Python, PyTorch, and transformer-based architectures

Other Requirements:

• Hands-on experience with vector databases and retrieval-augmented generation (RAG) architectures

• Strong awareness of AI system performance benchmarks (latency, speed, throughput)

• Experience with cloud computing and containerization (Docker, Kubernetes)

• Support language-specific adaptation for Traditional Chinese, Simplified Chinese, Japanese, or Korean markets

Responsibilities:

• Develop and deploy AI models for unstructured data with a focus on enterprise-scale performance

• Fine-tune, optimize, and deploy LLMs and multimodal models integrating distributed training

• Design and implement production-ready AI solutions ensuring scalability and low-latency inference

• Build and maintain end-to-end LLM Ops pipelines for training, deployment, and monitoring

• Implement vector search and retrieval-augmented generation (RAG) systems

Experience Requirements:

• 5+ years of hands-on experience in AI, Machine Learning, and Data Science

• Expertise in LLMs, including fine-tuning, distributed training, quantization, and pruning

• Experience working with OCR, ASR, and TTS applications in real-world deployments

• Proven experience deploying AI models in production at scale

• Proficiency in Python, PyTorch, and transformer-based architectures

Other Requirements:

• Hands-on experience with vector databases and retrieval-augmented generation (RAG) architectures

• Strong understanding of cloud computing and containerization (Docker, Kubernetes)

• Deep understanding of multimodal architectures and model distillation

Responsibilities:

• Develop and deploy AI models for unstructured data with a focus on enterprise-scale performance

• Fine-tune, optimize, and deploy LLMs and multimodal models integrating distributed training

• Design and implement production-ready AI solutions ensuring scalability and low-latency inference

• Build and maintain end-to-end LLM Ops pipelines for training, deployment, and monitoring

• Implement vector search and retrieval-augmented generation (RAG) systems

Benefits:

• Equity in a fast-growing startup

• Competitive benefits package

• Flexible time off policy

• Parental Leave

• A fun-loving and nerdy team

Experience Requirements:

• 5+ years building production machine learning systems

• Strong background in NLP and search/recommendation systems

Other Requirements:

• Deep expertise in classical and modern deep learning architectures

• Ability to take models from research to production

Responsibilities:

• Design and deploy end-to-end machine learning systems

• Build ML systems that analyze AI search behavior

• Partner with product managers to translate requirements into solutions

• Influence architecture decisions and improve team practices

Benefits:

• Equity in a fast-growing startup

• Competitive benefits package

• Flexible time off policy

• Parental Leave

• A fun-loving and nerdy team

Experience Requirements:

• 5+ years building production machine learning systems

• Strong background in NLP and search/recommendation systems

Other Requirements:

• Expertise across ML approaches (XGBoost, Transformers, RL)

• Proven ability to optimize models for latency and cost

Responsibilities:

• Design and deploy end-to-end machine learning systems

• Build systems that analyze AI search behavior

• Create algorithms for AI agent discovery and ranking

• Collaborate with product managers on technical solutions

Benefits:

• Revolutionizing the antiquated $800B+ Healthcare market

• Team of 50%+ ex-founders

• Work with urgency, autonomy, and ownership

• Solve first-of-their-kind problems in AI and medicine

• Help doctors reclaim time and patients get better care

Experience Requirements:

• Proven experience in agentic processes and LLM eval

• Strong Python and ML background (PyTorch, Hugging Face)

• Published research or deep applied work in LLMs

• Experience designing rigorous experiments

• Strong communication and technical writing skills

Other Requirements:

• Entrepreneurial core

• Elite teammate

Responsibilities:

• Build and scale automated evaluation pipelines

• Audit existing evaluation approaches

• Define benchmarks and automated pipelines

• Partner with engineering for CI gates

• Deliver repeatable evaluation framework

Benefits:

• Competitive salary and equity packages, including a 401k

• Remote-first culture — work from anywhere

• 100% Employer covered comprehensive health insurance

• Unlimited PTO policy

• Regular team events and offsites

Experience Requirements:

• 3+ years of experience in data science, machine learning, or a related field

• Proficiency in Python

• Experience working with large datasets using distributed systems like Apache Spark and Dask

Other Requirements:

• Fluency in cloud development (AWS, GCP, Azure, etc.) and MLOps is a plus

• Strong knowledge of machine learning algorithms and statistical techniques

• Excellent analytical and problem-solving skills

• Strong communication skills

Responsibilities:

• Develop and implement advanced fraud detection models

• Collaborate with cross-functional teams to design systems

• Analyze large volumes of data to identify patterns and trends

• Evaluate and optimize performance of existing models

• Stay up-to-date with latest trends in fraud detection and ML

Benefits:

• Competitive salary and equity packages, including a 401k

• Remote-first culture — work from anywhere

• 100% Employer covered comprehensive health insurance

• Unlimited PTO policy

• Regular team events and offsites

Experience Requirements:

• 3+ years of experience in data science, machine learning, or a related field

• Proficiency in Python

• Experience working with large datasets using distributed systems like Apache Spark and Dask

Other Requirements:

• Strong knowledge of machine learning algorithms

• Excellent analytical and problem-solving skills

• Experience in fintech, marketplaces, or financial services industry is preferred

• Knowledge of current fraud tactics and trends

Responsibilities:

• Develop and implement advanced fraud detection models

• Collaborate with cross-functional teams to design systems

• Analyze large volumes of data for fraud patterns

• Evaluate performance of existing fraud detection models

• Communicate complex data analysis to stakeholders

Benefits:

• Daily collaboration with founders

• Exposure to design and research leaders at top global brands

• Competitive cash and equity compensation

Experience Requirements:

• 5+ years in research, insights, or strategy roles

• Strong qualitative research experience

Other Requirements:

• Comfortable owning projects and client relationships independently

• Fluent in both numbers and narratives

• Clear, confident communicator

Responsibilities:

• Own customer relationships end-to-end as a research partner

• Independently scope, design, and run research projects

• Turn qualitative and quantitative data into clear, actionable insights

• Lead customer meetings, onboardings, and training sessions

• Create research and product-focused content and enablement materials

Benefits:

• Generous remuneration package

• Employee Stock Purchase Plan Enrollment

• 25 vacation days annually

• Pension plan

• Private health insurance

Experience Requirements:

• 8–10+ years in information science or related discipline

• Substantial time in consulting or advisory roles

• Knowledge of W3C semantic standards (RDF, SKOS, OWL)

• Consultative approach with enterprise customers

• Hands-on experience with semantic technologies, taxonomies, and ontologies

Other Requirements:

• Experience with text analytics and rule-based auto-tagging systems

• Practical experience with REST-based APIs

• Experience in highly regulated or content rich industries

• Familiarity with consultative frameworks (discovery, journey mapping)

Responsibilities:

• Lead in-depth discovery of business objectives and ecosystems

• Facilitate workshops on semantic modeling and taxonomy design

• Act as a trusted advisor to business and technical stakeholders

• Define and oversee design of thesauri, ontologies, and taxonomies

• Develop complex classification strategies

Benefits:

• Competitive salary

• Bonus

• Employee Stock Purchase Program (ESPP)

• Premium Collective Health Insurance Plan

• Premium Collective Pension Scheme

Experience Requirements:

• 8–10+ years in information science or related discipline

• Substantial time in consulting or advisory roles

• Knowledge of W3C semantic standards (RDF, SKOS, OWL)

• Consultative approach with enterprise customers

• Hands-on experience with semantic technologies

Other Requirements:

• Experience with text analytics and rule-based auto-tagging systems

• Practical experience with REST-based APIs

• Background working with cross functional teams (Product, CS, AI)

• Familiarity with consultative frameworks

Responsibilities:

• Lead in-depth discovery of business objectives and ecosystems

• Facilitate workshops and advisory sessions

• Define and oversee design of thesauri, ontologies, and taxonomies

• Develop complex classification strategies

• Lead complex client engagements as senior consultant

Education Requirements:

• Master's degree in data analytics, business analytics, or other closely related field

Experience Requirements:

• 1 year of related experience in data analytics

Responsibilities:

• Formulate hypotheses and test them using rigorous analytical methodologies and diverse frameworks

• Conduct advanced statistical analysis, machine learning, and data mining to drive product insights

• Develop and implement predictive models to support product strategy and decision-making

• Define key performance indicators (KPIs) and develop dashboards to monitor product performance

• Conduct A/B testing and other experimental methods to measure the impact of product changes

Experience Requirements:

• Training Stable Diffusion models to a high degree of fidelity

Other Requirements:

• Willingness to relocate within the Continental United States or work remotely

Responsibilities:

• Training Stable Diffusion models for use in professional applications

Benefits:

• Klue Enablement Program

• DEI education and initiatives

• Inclusive workplace culture

Benefits:

• Competitive base + performance-based compensation

• Unlimited PTO

• Generous healthcare coverage for you and your family

• Home office and productivity setup stipend

• Professional development budget and executive coaching access

Experience Requirements:

• 8-12 years of escalating levels of responsibility in a role blending data analytics and operations

• SQL/NoSQL/Python for data extraction at an expert level

• Spreadsheet-based workflows at an expert level

• Data visualizations

• Able to structure work at program level, independently managing toward a goal

Other Requirements:

• Project management across Research, Engineering, Product

• Data cleansing/debugging/RCA with messy data

Responsibilities:

• Identify and evaluate opportunities to improve data quality across the organization

• Develop creative solutions to resolve complex data issues

• Direct Research projects to uncover opportunities and drive progress on cleanup

• Prioritize Engineering efforts and track results over time to meet deadlines

• Leverage expert-level proficiency in Python, SQL, and NoSQL to transform, cleanse, and extract data