Benefits:

• Health, vision, and dental benefits

• Unlimited vacation

• Frequent team meet-ups in different parts of the world

• Equity options

Experience Requirements:

• Senior level experience with Python

• Senior level experience with backend Cloud services and Dev Ops

• Experience with deploying and serving of ML modes for inference

• Infrastructure as Code (IAC), Distributed Service Deployment, CI/CD, Docker

• Understands how to identify and fix performance bottlenecks

Other Requirements:

• Audio and FFMpeg experience

• ML experience

• Nvidia Triton Server, Kubernetes

• NodeJS, Javascript, Typescript

• RDS, Elasticache, PostgreSQL, Redis

• AWS CDK, ExpressJS, FastifyJS, Prisma JS, React

• Github Actions, AWS, DataDog

Responsibilities:

• Working with research team to deploy and optimize new ML models and architectures

• Update our python logic to improve our processing performance to work at scale

• Improve our processing pipeline to improve speed and reliability

• Inspecting and debugging Python code

• Improving our current backend and infrastructure code built with Python and NodeJS/Typescript languages Utilize the AWS CDK to update and maintain our cloud infrastructure Assist with efforts to deploy new infrastructure for new services Dynamically create and maintain our systems architectures in AWS via code using AWS libraries (Python and Javascript) Assist with brainstorming, writing documentation, and creating diagrams for our new architectural changes Help to maintain and improve the security and reliability of our services and ensure good engineering practices in compliance with our security policies

Experience Requirements:

• Proven track record of working with large-scale LLM and Deep Learning systems

• Strong programming skills, with a preference for versatile individuals

Responsibilities:

• Design and implement large-scale data pipelines that feed billions of high-quality tokens into LLMs

• Scale and distribute LLM training infrastructure to maximize efficiency

• Optimize evaluation pipelines to ensure accuracy and reliability

• Enhance inference infrastructure to reduce serving cost and latency while maintaining 99.9% uptime

• Continuously improve LLM performance and accuracy

Benefits:

• Selection of employer-covered medical plans, plus dental, vision, life insurance, and FSA

• Competitive parental leave policy

• Hybrid culture

• Company stock options, plus a 401k plan with employer contributions

• Learning and development stipend and generous PTO

Benefits:

• Selection of employer-covered medical plans, plus dental, vision, life insurance, and FSA

• Competitive parental leave policy

• Hybrid culture

• Company stock options, plus a 401k plan with employer contributions

• Learning and development stipend and generous PTO

Benefits:

• Selection of employer-covered medical plans, plus dental, vision, life insurance, and FSA

• Competitive parental leave policy

• Hybrid culture

• Company stock options, plus a 401k plan with employer contributions

• Learning and development stipend and generous PTO

Benefits:

• Free gym benefit

• Free lunches and fancy espresso machine in the office

• Company events including happy hours, sauna/cold plunge wellness retreats, Barrys bootcamp, and snow trips

Experience Requirements:

• 3+ years

Responsibilities:

• Architect and build cutting-edge AI data extraction systems

• Work directly with customers to tackle their toughest data challenges often with creative solutions

• Push the boundaries of AI tech and stay on the cutting edge of LLM developments.

• Own projects end-to-end from working with founders or customers on the product proposal, architecting, building, evaluating and testing, shipping to prod, and integrating with customers

Benefits:

• Remote-first

• Generous PTO

• Great Culture

• Amazing Benefits

• Career growth

Benefits:

• Remote-first

• Generous PTO

• Great Culture

• Amazing Benefits

• Career growth

Benefits:

• Remote-first

• Generous PTO

• Great Culture

• Amazing Benefits

• Career growth

Benefits:

• Remote-first

• Generous PTO

• Great Culture

• Amazing Benefits

• Career growth

Benefits:

• Remote-first

• Generous PTO

• Great Culture

• Amazing Benefits

• Career growth

Responsibilities:

• Build personalization engines

• Build generative models

• Build dashboards

• Build forecasting models

• Build chatbots

Benefits:

• 0.2% - 1.2%

Experience Requirements:

• 6+ years

Responsibilities:

• Create novel CV features that unlock new forms of video manipulation

• Build ML pipelines that understand and modify humans in video

• Transform research breakthroughs into production capabilities

• Design systems that make complex AI feel like magic to users

• Pioneer new approaches to fine-grained video control

Benefits:

• 0.1% - 1.2%

Experience Requirements:

• 6+ years

Benefits:

• 0.1% - 1.5%

Experience Requirements:

• 3+ years

Benefits:

• Comprehensive health, dental & vision plans

• Flexible paid time off

• 401K plans

• Remote-friendly

• Commuter benefits

Experience Requirements:

• 3+ years experience working as a Developer Advocate, Data Scientist, AI/ML Engineer, Solutions Engineer, or technical Product Manager/Marketer

Other Requirements:

• Working knowledge of generative AI, machine learning, and data science

• Technical experience with the LLM app development stack (e.g. agents, orchestration frameworks, vector databases, evaluation libraries) with proficiency in Python

• Engaged in technical communities via GitHub, Medium, DZone, Stack Overflow, Reddit, LinkedIn, etc.

• A data-driven creative who thrives in ideating and delivering on novel activities that earn the attention and trust of AI/ML practitioners

• A self-learner who isn’t daunted by technical complexity and welcomes the challenge to develop their own POV

• Excellent written and verbal communication

• Willingness to attend evening meetups and events in the SF Bay Area

Responsibilities:

• Create visibility of Arize and Phoenix content through thought-provoking daily technical content that is pushed out through AI community whether twitter, linkedin and reddit

• Build connections to Arize and Phoenix through viewership and consumption of AI related materials

• Build research, content and video snippets that resonate in the AI community and are related to Arize in areas of Evaluation, AI Assistants, AI Agents and AI Applications.

• Write code, build AI applications and write cookbooks that demonstrate the Arize product lines or other ecosystem tools that can be spread in the AI community

• Write the book on AI social marketing on how to turn consumption of AI content into OSS product usage & awareness

Benefits:

• Tight-knit, in-person team of PhD battery scientists and software engineers

• HQ in downtown San Francisco

• Work remotely from anywhere for up to four weeks per year

Experience Requirements:

• Want to push themselves to achieve extraordinary things

• Care strongly about helping our customers to succeed

• Feel a deep sense of pride over their craft

Benefits:

• Tight-knit, in-person team of PhD battery scientists and software engineers

• HQ in downtown San Francisco

• Work remotely from anywhere for up to four weeks per year

Experience Requirements:

• Want to push themselves to achieve extraordinary things

• Care strongly about helping our customers to succeed

• Feel a deep sense of pride over their craft

Benefits:

• Unreasonably hospitable and data-driven culture

• Empowered team members

• Trust and freedom

• Shared purpose and recognition

• Competitive compensation

Experience Requirements:

• 7+ years of experience

Other Requirements:

• Expert level proficiency in languages like Python, Java, C#, C++, Scala, etc.

• Strong data structures, algorithms, and OO software design and implementation skills

• Ability to learn and operate across full stack

• Experience as a creative and strategic thinker

• A “get stuff done” attitude

• A track record of successfully influencing product direction

• Skills in communicating with clear and concise, active listening and empathy skills, and a respectful, collaborative approach that earns the trust of your peers

• Authorized to work in the US

Responsibilities:

• Strategy: using your experience and understanding of how ML and NLP features are built to achieve state of the art results in real products, you will generate data-driven insights on how to evolve capabilities of Relyance AI

• Execution: create practical ML and NLP solutions, making customer-centric prioritization decisions to balance between immediate impact and long-term bets; partner, align, and collaborate with other engineering teams to implement features end to end, in particular throughout data engineering systems such as Airflow, VertexAI, BigQuery, etc.; or the Relyance backend

• Design: deeply understand how everything fits together; architect systems to balance scrappiness for the current needs with a forward-thinking outlook to incorporate state of the art NLP and ML techniques; continuously look for opportunities to automate and build tools to lower operational barriers

• Being a key member of the team solving its most complex problems with the simple, pragmatic solutions

Benefits:

• Unreasonably hospitable and data-driven culture

• Empowered team members

• Trust and freedom

• Shared purpose and recognition

• Competitive compensation

Experience Requirements:

• Experience building compilers or static code analysis tooling

• Strong software engineering experience and a firm grasp of CS fundamentals, data structures, and algorithms

• Experience building distributed/scalable backend infrastructure with a micro-services first design

• A high standard for production system quality

• Ability to demonstrate and incrementally build 100% confidence in all the layers/components you develop

Other Requirements:

• A deep sense of appreciation for the test-driven development methodology

• A self-directed environment with full ownership to design features end-to-end from scratch and the accountability that comes along

• Authorized to work in the US

Responsibilities:

• Designing and implementing a high-performance static code analysis service

• Working with Data Scientists/ML engineers to improve precision, robustness, and scalability of traditional static analysis algorithms using ML techniques

• Experimenting, prototyping, measuring, and making data-driven technology stack decisions

• Architecting and implementing microservices-based systems for distributed computing environments

• Leveraging strong CS fundamentals, data structures, and algorithms to solve complex engineering challenges