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

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

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

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

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

Experience Requirements:

• Proven track record of 3 years in a customer-facing role, preferably as a CSM in the GRC field

Other Requirements:

• In-depth understanding and experience of compliance regulations

• Experience with hitting retention targets

• Familiarity with compliance software and risk management practices

• Excellent verbal and written communication skills

• Strong interpersonal skills. Ability to build trust with clients at various levels

• Effective problem-solving abilities, finding solutions and resolving issues promptly

• Ability to prioritize tasks, and work efficiently in a fast-paced environment

• Self-motivated, proactive approach to identifying opportunities for driving client success

• English - Native level

Responsibilities:

• Develop and maintain strong, trusted relationships with key stakeholders within client organizations, understanding their unique needs and providing tailored support

• Anticipate client needs, provide proactive guidance, and offer solutions to enhance their compliance processes, addressing inquiries and issues in a timely manner

• Conduct training sessions to educate clients on the effective use of our tools, maximizing their understanding and utilization

• Identify opportunities for upselling or cross-selling additional services or products based on client needs, collaborating with sales teams as required

• Gather client feedback, analyze trends, and collaborate with internal teams to continuously improve our products and services

Benefits:

• A chance to be a part of a rapidly growing startup with a transformative technology

• Competitive salary with performance-based bonuses

• Opportunities for personal and professional growth

• Flexible working conditions with the ability to work remotely

Experience Requirements:

• Proven track record of B2B sales success, particularly in the North America region

• Demonstrable experience in selling SaaS or technology solutions to large enterprises

• Excellent leadership, communication, and interpersonal skills

• Ability to understand complex technical products and convey their value to non-technical stakeholders

Other Requirements:

• Fluent in English language

Responsibilities:

• Develop and execute a robust sales strategy to generate and convert B2B leads in the North America region

• Identify and engage potential clients in target industries, focusing on top-tier enterprises in tech, finance, healthcare, and the public sector

• Conduct market analysis to tailor approaches for different sectors and optimize penetration

• Establish and nurture long-term relationships with key decision-makers and stakeholders within target organizations

• Understand and address the unique needs and challenges of clients, proposing customized solutions using Dynamiq's platform