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:

• Always remote

Responsibilities:

• Help us research the future of remote work with AI

Benefits:

• Opportunity for professional development in the area of GenAI

• Private Medical insurance

• Multisport card

• Google certification paths

• Hybrid or remote location

Education Requirements:

• Master’s Degree, preferably in Linguistics, or a related field

Experience Requirements:

• A minimum of 3 years of experience in Data Science

• A minimum of 2 years of experience in NLP tasks

Other Requirements:

• Proficiency in PyTorch or another deep learning library

• Expert programming skills in Python

• Familiarity with the Numpy/Pandas libraries

• A solid understanding of machine learning concepts

• Knowledge of version control systems: git

• Demonstrated interest in and ability to work with advanced AI technologies

Responsibilities:

• Join us in development of cutting-edge projects, now embedded deeply into the realms of Generative AI (GenAI).

• Particularly focusing on advanced NLP/AI tasks, leveraging the newest Google Generative technologies, Langchain framework and exploring the potential of other GPT models.

• These activities represent a unique opportunity to work on the forefront of developing and innovative technologies on a global 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

Benefits:

• Work with the best experts in robotics, simulation using the latest technologies

• Opportunity to contribute to open source

• Competitive salary

• Cosy office space at Hala Koszyki, Warsaw

• Private medical care and sports card

Education Requirements:

• University degree in Computer Science, Machine Learning, Computer Vision or related field

Experience Requirements:

• Good understanding of Machine Learning and Deep Learning concepts

• Solid software engineering skills in Python

• Practical experience with ML / Data Science related frameworks and libraries such as PyTorch, Tensorflow, Numpy, Pandas and Matplotlib

Other Requirements:

• Familiarity with collaboration tools and methods such as git or CI

• Excellent communication and teamwork skills

• At least C1 level of English in both writing and speaking in order to communicate with foreign clients

Responsibilities:

• Develop and test Machine Learning tools for evaluation, data generation and model training

• Automate ML pipelines

• Work with perception layer of the AV/ADAS stack including LiDAR, camera, radar, ultrasonic, IMU and GPS sensors

• Develop perception algorithms for autonomous driving systems (object detection, classification and tracking)

• Work with synthetic datasets based on simulation engines

Education Requirements:

• Relevant PhD or MS preferred (e.g. Data Science, Computer Science, Statistics, Applied Statistics, Operational Research)

Experience Requirements:

• 4+ Years Experience in data science, quantitative modeling, or machine learning in a bank or fintech

Other Requirements:

• Required - Fluency in generalized linear models & machine learning methods and tools;

• Preferred - Experience with hypothesis testing

• Required - Fluency using Python and SQL; Preferred - Experience using PySpark and Pola.rs

• Consumer credit risk knowledge is preferred

• Above all, the ability to break down new and complex problems into fundamental and solvable components

Responsibilities:

• Develop credit risk predictive models based on cross-border consumer performance data or bank transaction data

• Develop models to categorize and group bank transactions to support multiple Nova Credit products

• Use bank transaction data to develop attributes for credit risk, income verification, or other products

• Collaborate with our engineering organization to guide reliable deployments of data science products; Perform continuous research into new data sources, variables, and modeling methodologies

• Develop and execute model monitoring solutions