AI Jobs

Benefits:

• Innovative company culture

• Flexible work schedules

• Family paid leave

• Paid healthcare for employees

• 401k

Education Requirements:

• Bachelor's degree in computer science, information security, risk management, and an MBA

Experience Requirements:

• 7+ years of experience with cyber risk management principles and frameworks such as CMMC, GDPR, HIPAA, ISO 27001, NIST CSF, PCI DSS, etc.

• 2+ years of experience in a consultative or advisory role

Other Requirements:

• Strong communication and interpersonal skills to effectively collaborate with mid-level to C-suite stakeholders

• Ability to assess the impact of security vulnerabilities and weaknesses in a company’s networks and quickly recommend changes to processes and technologies to remediate

• Experience in conducting risk assessments and developing risk mitigation strategies

• Understanding of incident response procedures and best practices

• Excellent analytical and problem-solving skills

• Relevant professional certifications (e.g. CISSP, CISA, CISM, CRISC) are a plus

• Ability to work independently and manage multiple tasks in a fast-paced environment

• Strong attention to detail

• Ability to work in a self-directed environment that is highly collaborative and cross-functional

Responsibilities:

• Participate in customer engagements to translate security concepts into risk impact

• Create impactful experiences for key customer stakeholders which include mid-level through C-suite security, risk, and finance professionals

• Assess the impact of security vulnerabilities and weaknesses in a company’s networks and quickly recommend changes to processes and technologies to reduce customer cyber risk

• Own the technical solution response to the customer and help deliver a comprehensive Resilience solution response that leverages the Resilience SaaS portal and your expertise

• Present the solution proposal to the customer, demonstrate how it reduces the customer’s risk and the financial impact of that risk reduction, and how the solution is differentiated from the competition

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

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:

• 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:

• 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

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:

• 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 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:

• 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

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:

• 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 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:

• 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 research domain knowledge in LLM safety techniques

• Extensive research experience in aligning, training, and/or attacking multiple different types of LLM models and architectures

• Adaptability and flexibility

Responsibilities:

• Spearhead an LLM research domain with a focus on safety, quality, explainability, evaluation, and/or adversarial attacks

• Push the envelope by developing novel techniques and research

• Co-author papers, patents, and presentations

• Lead research projects end-to-end

• Deliver generalizable, scalable, and reproducible algorithms

Education Requirements:

• MS/PhD degree in Computer Science, Statistics, Applied Mathematics, Computational Biology, Computational Chemistry or other related subject

• Will also consider BS degrees in these areas for candidates highly qualified across other requirements or with significant work experience

Experience Requirements:

• 2+ years of experience on machine learning teams, ideally at a start-up

• 4+ years of ML research experience in industry or academia, with strong familiarity with PyTorch

Other Requirements:

• Track record of contributing to novel methods for state-of-the-art Deep Learning (in industry or through publications) including large-scale Transformers, Graph Neural Nets, ConvNets, etc.

• Experience with Python is required

• Relevant experience working in a Linux/UNIX environment with basic data engineering and scripting abilities

• Ability to understand business problems and how to build models that can quickly drive value, while prioritizing your research efforts accordingly

• Clearly communicate modeling setup and results at various levels of abstraction

Responsibilities:

• Scientifically direct the design and training of large-scale, state-of-the-art Deep Learning systems

• Develop novel architecture and training paradigms to lead the industry in unsolved scientific problems

• Collaborate with content experts from other domains (e.g., chemistry, physics, biology) to enable innovative feature-engineering and novel cross-disciplinary approaches

• Actively contribute to top-tier ML conferences and journals and attend core ML conferences to stay connected with the community and current trends

Education Requirements:

• PhD in Chemical Biology, Proteomics, or related field

Experience Requirements:

• 5+ years in industry experience focused on small molecule drug discovery at pharmaceutical or biotech companies, with a track record in leading small molecule proteomic initiatives

Other Requirements:

• Proven experience in proteomics research and small molecule drug discovery

• Track record in designing and executing complex scientific experiments

• Computational affinity, worked with computational biologists

• Experience in managing a team of PhD researchers

• Familiarity with AI applications in proteomics and drug discovery

• Strong budget management skills

• Excellent communication skills, adept at summarizing scientific progress for various audiences

Responsibilities:

• Drive the scientific strategy, aligning our proteomics research with AI-driven drug discovery initiatives

• Lead and nurture a team of PhD researchers, promoting a culture of innovation and discovery

• Oversee lab operations and facilities, maintaining an environment that fosters excellence and safety

• Plan and steer ambitious proteomics experiments, making key decisions to shape our scientific trajectory

• Prudently invest in state-of-the-art lab hardware to keep us on the cutting edge of proteomics research Bridge the gap between lab teams and computational workstreams, fostering a synergistic environment that maximizes data utility Manage and optimize the lab budget, ensuring resources are strategically allocated Provide regular updates on scientific progress, keeping stakeholders informed and inspired

Education Requirements:

• MSc or PhD degree in computational biology, bioinformatics or a related field

Experience Requirements:

• Possess mixed academic and/or industrial experience, preferably in the biotech industry

Other Requirements:

• Strong background in computational structural or systems biology

• Strong programming skills in Python, R and/or other languages

• Experience building reproducible and scalable computational biology workflows

• Experience designing and applying machine learning models

Responsibilities:

• Develop pilot capabilities and create large-scale data pipelines from the ground up

• Collaborate with other teams across VantAI and partnering organizations to achieve project goals by contributing code, analyses, benchmarks, optimizations and ideas to ongoing research-driven projects

• Integrate biological insights into the next generation of AI/ML models for drug discovery

• Validate and interpret computational predictions by working closely with experimentalists

Education Requirements:

• MSc/PhD degree in Chemistry, Computational Chemistry, Biochemistry, Chemical Engineering, or another related subject

Experience Requirements:

• Minimum 2 years (PhD) or 4 years (MSc) of post-graduate experience in small-molecule drug discovery

Other Requirements:

• Proven track-record in advancing drug discovery projects using in-silico methods; strong background in rational drug design

• Ability to adapt well to a fast-paced environment and get things done by combining creativity, problem-solving skills, and a can-do attitude to overcome obstacles

• Extensive experience in large-scale virtual screening using structure and ligand-based methods for hit identification and optimization

• Strong programming skills with at least 2 years of experience using Python for data analysis

• Excellent written and verbal communication skills along with a strong desire to work in cross-functional teams

Responsibilities:

• Lead small-molecule drug discovery projects using internal and external Machine Learning and CADD tools

• Drive drug discovery programs forward by quickly developing scalable tools to address specific project needs

• Work independently and in collaboration with Medicinal Chemists to prioritize small-molecule designs, clearly communicating the decisions to interdisciplinary audiences

• Collaborate with experts from other fields (e.g., Medicinal Chemistry, Machine Learning, Computational and Structural Biology, etc.) to advance integrated in-silico discovery platforms

• Design and execute large-scale virtual screening campaigns using both ligand and structure-based approaches

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

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