Benefits:

• Potential for stock options

• Dynamic, agile work environment

• Forefront of AI and Security innovation

• Flexible hybrid work arrangement

• Healthy work-life balance

Experience Requirements:

• Proven expertise in LLMs and multi-agent approaches, including code generation

• Strong knowledge of prompt engineering techniques

• Proficiency in Python and experience using machine learning and AI frameworks

• Data mining knowledge

• Strong understanding of AI ethics

Other Requirements:

• Prior publications in conferences and journals (a plus)

• Excellent problem-solving skills

• Ability to work in a fast-paced startup environment

• Fluency in English (additional languages a plus)

Responsibilities:

• Implementing, integrating, benchmarking and deploying AI models for vulnerability detection

• Fine-tuning, testing, and optimizing models

• Collaborating with engineering and security researchers

• Collecting and analyzing datasets

• Contributing to the scalability and efficiency of AI

Responsibilities:

• Conducting research and developing algorithms for computer vision and machine learning.

• Implementing and testing algorithms on real-world data.

• Working with the engineering team to integrate algorithms into products and services

Benefits:

• Real world project experience: work on difficult & bleeding edge research problems, at scale

• Job opportunities: Subsequent fulltime or internship consideration

• Networking opportunities: access to internal events and introductions

Other Requirements:

• We do not accept talent agency submissions for this role

Responsibilities:

• Contribute to our models research or open source repos

• Developer relations: write documentation, give workshops, build demos & integrations

• Community building: coordinate events, support users

Benefits:

• We pay an “all-in” pay and you will cover your own insurance/medical from the amount

• 14 days leave (and unlimited sick days)

• Annual equipment budget (once 2 month probation has been completed)

Experience Requirements:

• Strong conceptual or mathematical understanding

• Experience with LLMs, including popular foundation models like llama, or Qwen

• [Bonus] Experience with Training LLMs beyond LORA/RAG

• [Bonus] Experience with software or hardware optimization techniques, e.g. flash attention

• [Bonus] Experience running LLMs in production (e.g. Triton Inference Server, etc)

Responsibilities:

• Train and fine-tune foundational LLM models

• Work with multiple modalities from vision to speech

• Push out insightful knowledge to the greater research & open source community

• Collaborate with engineers to productize research milestones

Benefits:

• We pay an “all-in” pay and you will cover your own insurance/medical from the amount

• 14 days leave (and unlimited sick days)

• Annual equipment budget (once 2 month probation has been completed)

Experience Requirements:

• Strong conceptual or mathematical understanding

• Experience with LLMs, including popular foundation models like llama, or Qwen

• Experience with Training LLMs beyond LORA/RAG

• Experience with software or hardware optimization techniques, e.g. flash attention

• [Bonus] Experience running LLMs in production (e.g. Triton Inference Server, etc)

Other Requirements:

• [Bonus] Expertise in Vision, Speech, and Robotics domains

Responsibilities:

• Train and fine-tune foundational LLM models

• Work with multiple modalities from vision to speech

• Push out insightful knowledge to the greater research & open source community

• Collaborate with engineers to productize research milestones

Experience Requirements:

• Experience with finetuning large language models

• 2+ years of experience working directly with large language models

• Deep knowledge of machine learning frameworks such as Pytorch and Deepspeed.

• Strong background in programming languages such as Python and C++

• Entrepreneurial spirit and willingness to adjust to dynamic customer needs

Other Requirements:

• Desire to grow quickly by going above and beyond expectations

Responsibilities:

• Design and run experiments on how to best finetune our in-house LLM models.

• Deploy these custom models end-to-end alongside our ML engineering team.

• Build new MLOps tools from 0 > 1 inside our existing platforms.

• Work closely with leadership and customers to understand large-scale recruiting and HR pain points, and develop state-of-art machine learning solutions for them.

• Write production ready code with speed, cost, and usability in mind

Benefits:

• Competitive compensation packages, including equity

• Remote work culture

• Health, dental and vision insurance

• Mental healthcare support and services

• 401(K) plan

Education Requirements:

• MS/Ph.D. in computer science, mathematics, or another quantitative discipline or exceptional work experience in ML engineering

Experience Requirements:

• 1-3 years ML Experience

• Experience developing machine learning-driven products at scale

• Experience solving problems using Machine Learning with PyTorch

• Exceptional understanding of designing ML systems in production at scale and applying a quantitative approach to identifying performance bottlenecks and cost/performance tradeoffs

• Practical experience with large data systems, data models, and batch and streaming data pipelines

Other Requirements:

• Ability to ramp up quickly on our tech stack, which includes GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js

• Extensive experience with model deployment, both static within applications and dynamic, using Flask, FastAPI, or similar frameworks

Responsibilities:

• Build and maintain a training pipeline for fine-tuning open-source LLMs

• Serve and Deploy the LLM on GPUs

• Formulate novel product issues to ML problems and propose and iterate on solutions quickly

• Triage customer issues to model/system shortcomings and communicate the complex architecture in a simple, comprehensible way to internal stakeholders

• Keep up with the fast-growing generative AI space and incorporate the latest developments into our system

Benefits:

• Competitive compensation packages, including equity

• Remote work culture

• Health, dental and vision insurance

• Mental healthcare support and services

• 401(K) plan

Education Requirements:

• Ph.D.in Computer Science, Mathematics, or another quantitative field or outstanding professional experience in machine learning engineering

Experience Requirements:

• Over 5 years of industry experience in machine learning, with a proven track record of developing ML-driven products at scale

• Experience building recommender systems, preferably in the e-commerce space

• Demonstrated expertise in tackling complex problems using machine learning frameworks like PyTorch

• A comprehensive understanding of ML system design in production environments, including a quantitative approach to evaluating performance bottlenecks and cost/performance trade-offs

• Hands-on experience with large-scale data systems, sophisticated data models, and batch and streaming data pipelines

Other Requirements:

• Quick adaptability to our technology stack encompasses GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js

• Deep experience in model deployment strategies, utilizing both in-application static methods and dynamic approaches with frameworks like Flask, FastAPI, or equivalents

Responsibilities:

• Architect and oversee development for novel product issues to ML problems and propose and iterate on solutions quickly

• Triage customer issues to model/system shortcomings and communicate the complex architecture in a simple, comprehensible way to internal stakeholders

• Build and maintain pipelines for fine-tuning open-source LLMs

• Serve and Deploy the LLM on GPUs

• Working with Product and Engineering counterparts, translate customer needs and business requirements into long term vision and roadmap at Wizard

Benefits:

• Competitive compensation packages, including equity

• Remote work culture

• Health, dental and vision insurance

• Mental healthcare support and services

• 401(K) plan

Education Requirements:

• MS/Ph.D. in computer science, mathematics, or another quantitative discipline or exceptional work experience in ML engineering

Experience Requirements:

• 3+ years ML Experience

• Experience developing machine learning-driven products at scale

• Experience solving problems using Machine Learning with PyTorch

• Exceptional understanding of designing ML systems in production at scale and applying a quantitative approach to identifying performance bottlenecks and cost/performance tradeoffs

• Practical experience with large data systems, data models, and batch and streaming data pipelines

Other Requirements:

• Ability to ramp up quickly on our tech stack, which includes GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js

• Extensive experience with model deployment, both static within applications and dynamic, using Flask, FastAPI, or similar frameworks

Responsibilities:

• Build and maintain a training pipeline for fine-tuning open-source LLMs

• Serve and Deploy the LLM on GPUs

• Formulate novel product issues to ML problems and propose and iterate on solutions quickly

• Triage customer issues to model/system shortcomings and communicate the complex architecture in a simple, comprehensible way to internal stakeholders

• Keep up with the fast-growing generative AI space and incorporate the latest developments into our system

Benefits:

• Competitive compensation packages, including equity

• Remote work culture

• Health, dental and vision insurance

• Mental healthcare support and services

• 401(K) plan

Education Requirements:

• MS/Ph.D. in computer science, mathematics, or another quantitative discipline or exceptional work experience in ML engineering

Experience Requirements:

• 5+ years ML Experience

• Experience developing machine learning-driven products at scale

• Experience solving problems using Machine Learning with PyTorch

• Exceptional understanding of designing ML systems in production at scale and applying a quantitative approach to identifying performance bottlenecks and cost/performance tradeoffs

• Practical experience with large data systems, data models, and batch and streaming data pipelines

Other Requirements:

• Ability to ramp up quickly on our tech stack, which includes GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js

• Extensive experience with model deployment, both static within applications and dynamic, using Flask, FastAPI, or similar frameworks

Responsibilities:

• Build and maintain a training pipeline for fine-tuning open-source LLMs

• Serve and Deploy the LLM on GPUs

• Formulate novel product issues to ML problems and propose and iterate on solutions quickly

• Triage customer issues to model/system shortcomings and communicate the complex architecture in a simple, comprehensible way to internal stakeholders

• Keep up with the fast-growing generative AI space and incorporate the latest developments into our system

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Experience Requirements:

• 5+ years of experience at leading chat, social media, or UGC product companies

Other Requirements:

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

• Excel at turning findings into actionable next steps and working with engineering to execute

• Enjoy leaning into high velocity experimentation

• Capable of standing up Character.AI's data science efforts, including the tools and systems that you will need to work effectively as we scale

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• at least PhD (or equivalent) research experience

Other Requirements:

• Write clear and clean production system code

• Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc)

• Track record of exceptional research or creative ML systems projects

• Comfortable writing model development code (PyTorch) for either training or inference

Responsibilities:

• Work on cutting-edge ML training and inference systems

• Optimize the performance and efficiency of our GPU clusters

• Develop new technologies that fine-tune leading consumer AI models

• Serve 20K+ QPS in production with LLMs

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• preferably 2+ years of industry experience

Other Requirements:

• Deep understanding of the “whole stack” when it comes to designing, training, evaluating and deploying machine learning models

• Have a track record of successfully owning projects from start to finish

• Have experience with generative models for various modalities

• Experience working with proven tools

• Experience working with diffusion models

Responsibilities:

• Determining the type of training data we need

• Developing new model architectures

• Creating new evaluations

• Writing fast inference algorithms

• Working with product teams to integrate feedback mechanisms into the product

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Education Requirements:

• at least PhD (or equivalent) research experience

Other Requirements:

• Write clear and clean production-facing and training code

• Experience working with GPUs (training, serving, debugging)

• Experience with data pipelines and data infrastructure

• Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc)

• Track-record of exceptional research or creative applied ML projects

Responsibilities:

• Develop alignment algorithms and loss functions

• Write data pipelines to process diverse web data

• Identify quality signals to understand our model’s performance

• Design sampling algorithms to improve serving efficiency

Benefits:

• Top-notch health coverage

• 401(K) contribution

• Paid leave (up to 20 weeks)

• 4 weeks PTO

• Daily in-office catering & monthly Doordash stipend

Experience Requirements:

• 4+ years of experience supporting the infrastructure within an ML environment

Other Requirements:

• Experience in developing tools used to diagnose ML infrastructure problems and failures

• Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage)

• Experience working with GPUs

Responsibilities:

• Provide infrastructure support to our ML research and product

• Build tooling to diagnose cluster issues and hardware failures

• Monitor deployments, manage experiments, and generally support our research

• Maximize GPU allocation and utilization for both serving and training

Benefits:

• Remote work option

• Ability to grow with a dynamic startup and work on an exciting product

• Freedom to experiment with your ideas – we’re always open to suggestions and appreciate personal initiative

Experience Requirements:

• At least 2 years of Python development experience

• Experience building production grade machine learning solutions

• Experience developing REST APIs

• Knowledge of TensorFlow, pytorch, pandas and other popular ML packages

Other Requirements:

• Experience with natural language processing

• Experience developing recommender systems

• Experience with Docker, Kubernetes or other ML deployment strategies

Responsibilities:

• Develop an industry-leading natural language processing (NLP) system

• Develop travel product personalization engine

• Design, deploy, and monitor ML models in production

• Build APIs around machine learning models

Benefits:

• Remote work option

• Ability to grow with a dynamic startup and work on an exciting product

• Freedom to experiment with your ideas – we’re always open to suggestions and appreciate personal initiative

Experience Requirements:

• At least 2 years of experience in a similar role

• Experience working with data in Python

• Experience with Looker, Tableau, or other business analytics tools

• Knowledge of SQL and NoSQL databases

Responsibilities:

• Find meaningful business insights in large-scale data

• Visualize the data, create dashboards and reports for the business

• Import and transform data for machine learning models

• Optimize the data collection, storage, and analysis on a large scale

Benefits:

• Fully remote

• Flexible hours

• SF and London in-person locations (quarterly)

• Competitive salary ($100,000-$185,000)

• Higher-than-average equity

Education Requirements:

• PhD in Mathematics (for Research Scientist)

• PhD in Atomic/Molecular Physics, MSc (for CTO)

• PhD in Statistics, MD (for Research Engineer)

Experience Requirements:

• Experienced researcher in math, physics, CS, or equivalent quantitative field (for Research Scientist)

• Ability to quickly grasp developments in modern AI systems (for Research Scientist)

• Ability to start with an open problem, research a solution, and build evaluations (for Research Scientist)

Responsibilities:

• Figuring out how to research and reason about hard, judgment-laden questions

Benefits:

• Fully remote

• Flexible hours

• SF and London in-person locations (quarterly)

• Competitive salary ($100,000-$185,000)

• Higher-than-average equity

Education Requirements:

• PhD in Statistics, MD (for Research Engineer)

• PhD in Atomic/Molecular Physics, MSc (for CTO)

• PhD in Mathematics (for Research Scientist)

Experience Requirements:

• Researcher who can rapidly engineer systems based on papers (for Research Engineer)

• Ability to design and implement a pipeline or agent and rigorously evaluate solutions (for Research Engineer)

• Experience in or ability to quickly learn GCP + Azure, Dagster, Python, Supabase (for Research Engineer)

Responsibilities:

• Building AI systems that reliably answer hard reasoning tasks

• Designing and implementing pipelines or agents

Education Requirements:

• Bachelor's or Master's degree in Marketing, Business, IT

Experience Requirements:

• Final-year students or fresh graduates

Other Requirements:

• Programming, Problem-solving, Technical Documentation, Data Analysis

Responsibilities:

• Research Support

• Prototyping

• Problem Solving

• Algorithm Enhancement

• Documentation