AI Jobs

Benefits:

• Competitive compensation including equity

• Retirement and Employee Stock Purchase Plans

• Flexible paid time off

• Comprehensive benefit plans

• Professional development and yearly learning stipend

Education Requirements:

• Bachelor’s degree in Computer Science, Data Science, Mathematics, or Engineering

• Master’s or PhD preferred

Experience Requirements:

• 3–5+ years of hands-on experience as a Data Scientist or ML Engineer

• Experience in production environments and large-scale data

• Proficiency in Python and ML libraries (TensorFlow, Keras, etc.)

Other Requirements:

• Follow strong development practices (Git, CI/CD, code reviews)

• Able to explain complex technical ideas persuasively

• Entrepreneurial problem-solver

• Continuous learner interested in industry trends

Responsibilities:

• Partner with customers to ensure their success with BrazeAI

• Develop reusable data pipelines and components

• Work with RL pipeline development team to advance algorithms

• Contribute to product strategy through customer-facing insights

• Provide technical expertise for measurable customer outcomes

Benefits:

• Competitive compensation including equity

• Retirement and Employee Stock Purchase Plans

• Flexible paid time off

• Comprehensive medical, dental, and vision plans

• Yearly learning stipend

Education Requirements:

• Bachelor’s degree in Computer Science, Data Science, Mathematics, or Engineering

• Master’s or PhD preferred

Experience Requirements:

• 3–5+ years of hands-on experience as a Data Scientist or ML Engineer

• Experience in customer-facing roles preferred

• Strong technical expertise in Python and SQL

Other Requirements:

• Modular and documented coding skills

• Customer collaborator and clear communicator

• Knowledge of DevOps tools is a nice-to-have

• Skilled in machine learning pipelines and model deployment

Responsibilities:

• Collaborate with customer Analytics/BI teams on data integration

• Extend product capabilities and develop reusable components

• Advance reinforcement learning (self-learning) algorithms

• Translate technical concepts into business value

• Ensure measurable outcomes and long-term customer success

Benefits:

• Competitive salary packages with equity options

• Remote-first culture with flexible hours

• Comprehensive health coverage

• Wellness stipends and mental health support

• Professional development budget

Responsibilities:

• Explore and develop novel approaches to NLP and conversational AI

Benefits:

• Comprehensive health, dental, and vision insurance

• The latest and best office equipment

• Competitive salary, equity, and benefits package

• Flexible work environment

• Unlimited, flexible time off

Education Requirements:

• Currently pursuing a Bachelor’s, Master’s, or Ph.D. in Computer Science, Statistics, or Data Science

Experience Requirements:

• Solid foundation in statistics and core machine learning concepts

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn)

• Proficiency in SQL

• Prior professional or internship experience in data science

Other Requirements:

• Fluent in both English and Mandarin preferred

Responsibilities:

• Support development and validation of machine learning models

• Assist in building LTV and revenue forecasting models

• Design and analyze experiments to evaluate model effectiveness

• Conduct exploratory data analysis

• Build dashboards and data narratives

Experience Requirements:

• Relevant publications

• 2+ years of experience in a research role in industry

• Proven track record of contributions to open source language, audio, or video models

• 2+ years of experience contributing to the training and/or fine-tuning of models

Other Requirements:

• Expertise in the Python ecosystem and popular ML libraries and tools (e.g. PyTorch)

• Experience writing robust and maintainable production-ready code

• Comfort iterating quickly on new and uncertain research directions

Responsibilities:

• Build state-of-the-art speech-language models (SLMs)

• Build software systems for distributed training, inference, and benchmarking

• Massive-scale data collection, storage, preprocessing, and analysis

• Solve AI research problems at industry scale

Education Requirements:

• Ph.D. or M.S. in Chemistry, Materials Science, Chemical Engineering, or a related field

Experience Requirements:

• 3-5 years of industrial analytical chemistry experience

• Demonstrated expertise in tool management and method development

• Proven ability to solve complex analytical challenges

• A quality-first approach to method development and troubleshooting

• Detail-oriented with excellent project management skills

Other Requirements:

• Expertise in Gas, liquid, or ion chromatography

• Expertise in Mass spectrometry

• Expertise in Trace metals analysis by ICP-MS or OES

• Experience with lab quality standards (e.g., ISO 17025, ASTM, GMP)

• Experience supporting tool installation and qualification

Responsibilities:

• Own and ensure the success of projects in ICP-MS, ICP-OES, LC-MS, and GC-MS

• Develop and validate new analytical methods for diverse applications

• Interpret data, compile findings, and present results in customer-facing reports

• Assign and delegate projects, write SOPs, and train junior staff

• Maintain and optimize instrument performance and interface with vendor support

Benefits:

• Competitive pay

• health insurance

• daily breakfast

• weekday lunches

• Friday team lunch

Education Requirements:

• Bachelor’s degree in Engineering or a related field.

Experience Requirements:

• Minimum 2+ years of experience in Big Data.

Other Requirements:

• Proficient in SQL with the ability to write complex queries

• Strong Python skills (Pandas, NumPy, etc.)

• Excellent analytical and critical thinking abilities

• Familiarity with Google/AWS/Azure Cloud & Apache Spark

• Familiarity with Air Flow and Shell scripting

Responsibilities:

• Understand and leverage data assets with product and engineering teams

• Set up data processing pipelines using SQL, Python, Spark, and cloud

• Develop and optimize strategies for data storage and retrieval

• Research alternative data sources and assess their integration

Benefits:

• Competitive pay

• health insurance

• daily breakfast

• weekday lunches

• Friday team lunch

Education Requirements:

• Bachelor’s degree or higher in Business, Analytics, Statistics, or Math.

Experience Requirements:

• 2+ years of experience in data science or marketing science

Other Requirements:

• Highly analytical mindset with strong problem-solving skills

• Track record working with mid-market and enterprise brands

• Ability to communicate complex data science concepts simply

• Proficiency in leveraging social media for thought leadership

Responsibilities:

• Solve measurement needs using Marketing Mix Modeling and attribution

• Articulate value propositions of the UMM platform to brands

• Study customer business goals to offer expert recommendations

• Manage customer accounts and communications

• Contribute to product roadmap and feature development

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 (AWS SageMaker, Hugging Face, transformers, PyTorch)

• Fluent in written and spoken English

Responsibilities:

• Work with subject matter experts and product owners to determine what questions should be asked

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

• Develop and tune Machine Learning models

• Utilize, adopt, and fine-tune Language Models

• Stay current in the field and read research papers

Benefits:

• Health Care Coverage

• Education Reimbursement

• Competitive Paid Time Off

• Self-Care Days

• Parental Leave

Education Requirements:

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

Experience Requirements:

• At least 10 years of industry experience in Machine / Deep Learning, Computer Science and Software Engineering

Other Requirements:

• Academic publications in peer reviewed conferences (NeurIPS, ICML, ICLR, etc.)

• Deep Learning development skills (PyTorch, PyTorch Lightning, Ray, AWS SageMaker)

• Understanding of Language Models and fine-tuning

• Fluent in written and spoken English

Responsibilities:

• Research and develop Machine Learning models and optimize for production

• Explore ongoing product issues and recommend innovative ML/AI based solutions

• Curate and generate optimal datasets following responsible practices

• Investigate weaknesses of models in production and work on pragmatic solutions

• Modify and fine-tune off the shelf models or develop novel models

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:

• At least 5 years of industry experience in Machine / Deep Learning, Computer Science and Software Engineering

Other Requirements:

• Academic publications in peer reviewed conferences

• Machine / Deep Learning development skills (PyTorch, Hugging Face, Transformers)

• Understanding of Language Models and industry-standard LM families

• Fluent in written and spoken English

Responsibilities:

• Research and develop production grade Machine Learning models

• Recommend innovative ML/AI based solutions for product challenges

• Curate and generate optimal datasets including SQL, no-SQL and web data

• Investigate weaknesses of models in production

• Fine-tune off the shelf models including LLMs via API and local hosting

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