Experience Requirements:

• Deep domain knowledge in LLM safety techniques

• Extensive experience in designing, training, and implementing multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Own an LLM vertical with a focus on a specific safety domain

• Generate high quality synthetic data, train LLMs, and conduct rigorous benchmarking

• Deliver robust, scalable, and reproducible production code

• Push the envelope by developing novel techniques and research

• Co-author papers, patents, and presentations

Experience Requirements:

• Deep domain knowledge in privacy-preserving ML

• Practical experience in techniques to attack or defend ML models

• Extensive experience in implementing multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Own an ML privacy vertical

• Collaborate with our engineering team to deliver real-world applications

• Generate high quality synthetic training data, train LLMs, and conduct rigorous evaluation and benchmarking

Experience Requirements:

• Domain knowledge in LLM evaluation and data curation techniques

• Extensive experience in designing and implementing LLM benchmarking

• Adaptability and flexibility

Responsibilities:

• Own LLM evaluation processes and methods

• Generate high quality synthetic data, curate labels, and conduct rigorous benchmarking

• Deliver robust, scalable, and reproducible production code

• Push the envelope by developing methods for benchmarking

• Co-author papers, patents, and presentations

Experience Requirements:

• Deep domain knowledge in LLM safety and/or evaluation techniques

• Extensive experience in designing, implementing, and maintaining production-ready ML code

• Comfortability with leading end-to-end projects and collaborating with researchers and engineers

• Adaptability and flexibility

Responsibilities:

• Work at the intersection of ML and Engineering

• Perform rigorous testing of the product features

• Push the envelope by implementing novel techniques

• Work closely with our policy, product, and engineering teams

Experience Requirements:

• Significant experience deploying and securing production AI/ML infrastructure

• Deep understanding of popular security posture management tools and practices

• Strong familiarity with AI/ML concepts

• Previous experience in security services setup or at a large SaaS security company is highly desirable

Responsibilities:

• Work directly with customers to assess and enhance their AI/ML security posture

• Design and implement architectural patterns and proof of concepts

• Collaborate with cross-functional teams

Education Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field. Master’s degree preferred

Experience Requirements:

• 8+ years of experience in a technical pre-sales or sales engineering role

• Deep understanding and hands-on experience with AI, machine learning, and cloud computing technologies

• Proficiency in container technologies such as Docker and Kubernetes

• Proven track record of leading successful technical sales engagements

• Strong communication and presentation skills

Responsibilities:

• Build and Lead Sales Engineering Team

• Technical Sales Leadership

• Customer Engagement

• Product Alignment

• Product Evangelism

Experience Requirements:

• Experience with managing teams, projects, or products

• Experience with machine learning topics is a plus

• Experience leading ML or engineering teams in financial services is a plus

Responsibilities:

• Develop strategies to most effectively address enterprise customer needs

• Prepare presentations and materials

• Identify and quantify pain points and needs

• Execute plans for successfully meeting customer deliverables

Education Requirements:

• Bachelor’s degree in Business Administration, Marketing, or a related field

Experience Requirements:

• At least 8-10 years of experience in customer success

• Strong understanding of customer success metrics

• Excellent interpersonal and communication skills

• Demonstrated ability to manage and inspire a team

• Proficient in CRM and Customer Success software platforms

Responsibilities:

• Build and lead Customer Success Team

• Customer Relationship Management

• Customer Onboarding and Adoption

• Customer Advocacy

• Retention and Growth Strategies

Experience Requirements:

• 3+ years of experience developing and managing scalable services in Kubernetes

• Proficiency in Kubernetes, cloud services, and modern DevOps practices

• Proven track record of collaborating with customers

• Strong programming skills in Python or other relevant languages

Responsibilities:

• Design, develop, and maintain our Kubernetes-based infrastructure

• Take full ownership of the infrastructure

• Be innovative, apply industry best practices

• Develop and maintain automated testing frameworks and CI/CD pipelines

Experience Requirements:

• 5+ years of experience developing user interfaces with TypeScript, React

• Demonstrated experience in front-end architecture

• Strong proficiency in translating design mockups

• Experience with state management solutions

• Solid understanding of accessibility standards

Responsibilities:

• Architect, design, and develop front-end systems

• Rapidly translate Figma mockups into fully functional user interfaces

• Lead the design reviews

• Optimize applications for speed, scalability, and cross-browser compatibility

• Implement and manage state management solutions

Experience Requirements:

• 4+ years in DevOps or related field

• Proficiency in IaC and CI/CD automation tools

• Strong expertise in managing Kubernetes clusters

• Advanced programming skills in Python and Bash

• Excellent analytical and troubleshooting skills

Responsibilities:

• Build and improve our CI/CD pipelines

• Manage our CD processes using ArgoCD

• Manage our entire AWS infrastructure using Terraform

• Implement and manage monitoring and alerting

• Implement and maintain security best practices

Experience Requirements:

• Demonstrated success in delivering and maintaining AI products at scale

• Deep knowledge of best engineering practices

• Capability of delivering industry-leading AI solutions

• Strong communication and collaboration skills

Responsibilities:

• Lead the engineering team to design, develop, and deploy high-performance, secure, and reliable ML services

• Partner closely with the ML team to streamline and optimize the transition from experimentation to production

• Deeply understand customer needs and industry trends

• Work directly with customers to deliver tailored solutions

• Establish yourself as a thought leader in the AI safety and compliance domain

Benefits:

• enhanced maternity, paternity, adoption, and shared parental leave

• private medical and dental insurance for yourself and any dependents

• flexible working options

• healthy food

• on-site gym

Education Requirements:

• BS degree in Computer Science, Engineering, related fields or equivalent practical technical experience

Experience Requirements:

• Excellent technical understanding and communication ability, with the ability to distil sophisticated technical ideas to their essence

• Skilled at navigating, updating and defining complex processes

• Initiative to solve problems with solutions that are repeatable, scalable and sustainable

• Proven strong stakeholder management skills

• Comfortable dealing with ambiguity and able to thrive in a dynamic environment

Other Requirements:

• A curiosity about Google DeepMind's mission and AI / Machine Learning

• Flexible, adaptable and highly responsive to the needs of the project, team and wider group

• Knowledge of data centre infrastructure and operations

• Knowledge of cloud infrastructure

Responsibilities:

• Creating and scaling processes for collecting data on future ML hardware requirements, including next-gen ML accelerators and cloud infrastructure

• Partnering with portfolio managers and data analysts to allocate capacity across projects effectively and in line with company priorities

• Providing best practices to researchers and engineers in areas such as resource availability, efficiency, scaling & performance

• Producing regular targeted communications to leadership, research and engineering teams

• Assisting with new ML hardware/software pilot programs

Benefits:

• enhanced maternity, paternity, adoption, and shared parental leave

• private medical and dental insurance for yourself and any dependents

• flexible working options

• healthy food

• on-site gym

Education Requirements:

• Bachelor’s degree or equivalent practical experience

Experience Requirements:

• Proven track record of success in product marketing, strategic consulting or product management

• Experience developing compelling product narratives, building impactful GTM plans and managing highly complex product launches and marketing campaigns

• Previous marketing experience in AI or other emerging technologies is ideal

Other Requirements:

• Passionate, creative storyteller who is well versed in the AI landscape, keeping up with the latest AI trends

• Proven track record of delivering impactful stories, product messaging and positioning, and scaled launches in a fast-paced, dynamic environment

• Successful at working collaboratively across highly technical teams including researchers, engineers and product managers across multiple time zones

Responsibilities:

• Develop and execute the product marketing and GTM strategy and plans for GDM models and prototypes that aligns with product roadmap

• Collaborate closely with GDM research and product teams on model-to-product roadmaps, GTM approach and ensure xGoogle alignment

• Execute a drumbeat of model and prototype launches throughout the year and deliver GDM’s narrative and presence at I/O, NEXT and other marquee Google moments

• Work with a team of internal and external creative strategists, content producers and agency resources to develop demos and other supporting marketing materials like blog posts, social media assets and executive presentations, ensuring all assets are delivered on-time, on-brand and in-budget

Education Requirements:

• Master/undergrad degree in biology, chemistry, or similar

Experience Requirements:

• Strategy & Operations experience, ideally in a high-pressure multi-stakeholder environment (e.g., consulting, M&A, private equity, etc.)

• Hands-on team management experience

Responsibilities:

• Design and implement roadmap to set up a new experimental hub for VantAI

• Manage day-to-day operations with the internal team to achieve roadmap milestones

• Manage relationships with external collaborators and stakeholders

Education Requirements:

• Experience and academic background in bio/chem engineering, computational chemistry/biology/biophysics

Experience Requirements:

• Experience working on drug discovery projects

Other Requirements:

• Developing cheminformatics workflows

• RDKit, VS, protein-protein docking, Rosetta, MD, ML

• Ability to break apart existing code; solve ad hoc problems with little help

• Willingness to work with existing codebases

• No task too big or small; strong sense of independence and ownership

Responsibilities:

• Shaping our product by spearheading new features and services

• Developing software tools to automate or improve processes ranging from data ingestion pipelines to bespoke cheminformatics workflows

• Contributing to the culture of a rapidly growing company

• Being challenged by your colleagues and learning something new every day

Experience Requirements:

• Experience working in complex codebases and cloud-native architectures

• Container orchestration and Kubernetes cluster development

• Demonstrated experience creating and managing infrastructure for ML model registry, training, inference and deployment infrastructure

• Strong familiarity with best practices and current state of the art for ML infrastructure

• Experience supporting large-scale model architectures with complex environment requirements

Other Requirements:

• Data architecture and engineering

• Demonstrated experience with parallel computing and distributed model architectures

• Ability to break apart existing code; solve ad hoc problems with little help

• Willingness to work with existing codebases

• No task too big or small; strong sense of independence and ownership

• Provide guidance and opinions on implementation/considerations, while having a willingness to compromise

Responsibilities:

• Shaping our product by spearheading new features and services

• Developing software tools to automate or improve processes ranging from data ingestion pipelines to bespoke cheminformatics workflows

• Contributing to the culture of a rapidly growing company

• Being challenged by your colleagues and learning something new every day

Experience Requirements:

• Experience working in complex codebases and cloud-native architectures

Other Requirements:

• IAM policy development and automation

• Container orchestration and Kubernetes cluster development

• Experience supporting large-scale scientific workflows/compute environments

• Data architecture and engineering

• Ability to break apart existing code; solve ad hoc problems with little help

• Willingness to work with existing codebases

• No task too big or small; strong sense of independence and ownership

• Provide guidance and opinions on implementation/considerations, while having a willingness to compromise

Responsibilities:

• Develop large-scale scientific workflows

• Provide support to our scientists on existing workflows and proactively identify areas for increasing automation to reduce inefficiencies

Education Requirements:

• B.S./M.S. in Life Science(s), Computer Science, Computational Chemistry, Computational Biology, Engineering, Business or related fields

Experience Requirements:

• 5-10 years of work experience in a biotech or pharmaceutical environment

• 1-3 years in a project management role

Other Requirements:

• Demonstrated ability to work cross-functionally with multiple teams including Biology, Chemistry, Comp Bio, Comp Chem, Software Engineering and Machine Learning

• Ability to manage multiple projects simultaneously and prioritize competing demands

• Familiar with drug development pipelines and experience managing collaborations with external partners

• Knowledge of project management tools and methodologies (PM certification is a plus)

Responsibilities:

• Lead cross-functional teams to ensure successful launches of collaboration projects

• Align with external partners on project objectives, timelines and deliverables

• Partner with project leaders to define scope, develop project plans and timelines, monitor and communicate project progress to stakeholders

• Proactively manage project schedules, identify risks and help solve issues in a timely manner

• Facilitate meetings, prepare meeting agendas and meeting minutes Foster effective communication and collaboration amongst various parties Manage project documentation and ensure compliance Develop and implement project management best practices Play an alliance manager role, building and maintaining relationships between internal team members and external partners

Education Requirements:

• Currently enrolled in or a recent graduate from an undergraduate or graduate program in Computer Science

Experience Requirements:

• Proven experience in software development, with a strong foundation in Python and full-stack development

• Ability to efficiently manage multiple data processing workflows and demonstrate proficiency in data visualization

• Quick to learn and apply new concepts in biology and preclinical drug discovery strategies

• Strong team player and effective individual contributor

Responsibilities:

• Support the Target Prioritization Team in building a new prioritization framework suited for the future of proximity modulation, particularly to identify and rank novel therapeutic strategies

• Develop methods to integrate qualitative scientific knowledge and market analyses into scorable metrics

• Leverage proprietary protein-protein interaction data to link biological pathways to human diseases and uncover druggable vulnerabilities

• Create novel computational tools to retrieve, combine, and analyze diverse datasets

• Bridge the gap between technical and non-technical team members, applying insights from cutting-edge research to evaluate drug targets in real-time