About Us Udacity is now an Accenture company, and exciting things are happening! 🚀 We are on a mission of forging futures in tech through radical talent transformation in digital technologies. We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more. Our rapidly growing global organization is revolutionizing how the enterprise market bridges the talent shortage and skills gaps during their digital transformation journey. About Us Udacity is now an Accenture company, and exciting things are happening! 🚀 We are on a mission of forging futures in tech through radical talent transformation in digital technologies. We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more. Our rapidly growing global organization is revolutionizing how the enterprise market bridges the talent shortage and skills gaps during their digital transformation journey. In our mission toward powering careers through tech education, we are doubling down on the support that we offer to our students. As a part of this, we are looking for experienced AI professionals to mentor learners enrolled in our business-focused AI programs. Our learners are typically managers, executives, and other senior professionals responsible for AI initiatives inside their organizations. They are working through structured Udacity curriculum and applied projects. Mentors are there to deepen understanding, provide context from real-world experience, and help connect course concepts to how AI is actually deployed. This is not a purely academic role. We’re looking for practitioners who have actually worked with AI in production environments and can speak candidly about what works, what fails, and why. Responsibilities: As an AI Fundamentals & Applied AI Tech Talk Speaker, you will deliver engaging, structured learning sessions that help client teams understand and adopt AI in practical, responsible ways. You will work with our internal team to tailor sessions to the audience’s role, seniority, and learning goals. You could be responsible for delivering any of the following: Delivering live AI learning sessions for audiences ranging from 10-100 participants , including entry-level cohorts, cross-functional teams, and leadership groups Teaching AI fundamentals in a clear and accessible way (AI vs ML vs GenAI, what LLMs are, limitations, risks, and best practices) Demonstrating practical AI use cases that map to real work (productivity, analysis, writing, customer support, engineering workflows, and decision-making) Training employees on role-based AI adoption , including how to use AI responsibly and effectively in their current role Delivering leader-focused AI sessions that cover strategy, governance, risk, and organizational adoption (not just tools) Facilitating Q&A and discussion , helping teams apply concepts to their day-to-day work and current challenges Partnering with internal stakeholders to align talk content with audience level, learning objectives, and delivery expectations Maintaining high delivery quality and reliability , including preparation, responsiveness, and adherence to session timeline Required Qualifications: Preferred Qualifications: Experience implementing GenAI solutions (OpenAI, Anthropic, Azure OpenAI, etc.) Experience with Retrieval-Augmented Generation (RAG) Experience with AI evaluation or model monitoring Experience with enterprise AI adoption programs Experience teaching non-technical audiences Background in security/privacy/compliance Why should you apply? Gain recognition for your technical knowledge Earn additional income Contribute to a vibrant, global student community Stay updated on the latest cutting-edge technologies There are only Limited open positions , so please don’t wait too long to apply! Note: Technical Mentors work independently and set their own schedule. However, the above-mentioned opportunities are subjected to a specific schedule and agenda .  If selected you would be provided with access to the Mentorship Nanodegree program. You are requested to graduate from the Mentorship Nanodegree in order to be onboarded as a Technical Mentor. Compensation at Udacity, an Accenture company, varies depending on a wide array of factors, which may include but are not limited to location, role, skill set, and level of experience. As required by local law, Udacity, an Accenture company, will provide a reasonable range of compensation. We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. Accenture Equal Opportunity Statement Udacity, an Accenture company, is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities, and is committed to providing veteran employment opportunities to our service men and women. Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States. Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment. Udacity's Values Obsess over Outcomes - Take the Lead - Embrace Curiosity - Celebrate the Assist Udacity's Terms of Use and Privacy Policy

About Absci Absci is a clinical-stage biotechnology company advancing novel therapeutics using generative AI. Our Integrated Drug Creation™ platform combines cutting-edge AI models with a synthetic biology data engine, enabling the rapid design of innovative therapeutics that address challenging therapeutic targets. Absci is a global company headquartered in Vancouver, WA, and maintains offices in New York City, Switzerland, and Serbia. Learn more at www.absci.com or follow us on LinkedIn (@absci), X (@Abscibio), and YouTube. About the role Absci is seeking AI Scientists to join its team of experts advancing generative and predictive modeling at the intersection of machine learning and drug discovery. As an AI Scientist, you will develop AI models that generate and evaluate antibody therapeutic candidates. We are looking for exceptional contributors with backgrounds in deep learning, protein design and engineering, natural language processing, computer vision, and molecular dynamics to develop innovative approaches to creating and assessing therapeutic antibodies in silico . Absci’s computational teams (including its AI Scientists) develop and validate software platforms for antibody design and in silico assessment, while its Wet Lab teams experimentally validate its AI platforms, and its Drug Creation teams translate experimentally-validated AI designs into clinically-viable therapeutics. The ideal AI Scientist candidate will : Care as much about solving the technical problems related to designing antibody therapeutics as they do about translating solutions to the clinic; Use their expertise to influence the AI team's research agenda while maintaining high levels of responsibility and accountability for their work; Demonstrate their curiosity about the problems we are attempting to solve by developing proficiency in disciplines that fall outside their own areas of expertise, constantly increasing the scale and impact of their contributions; Invest in ensuring their work is accessible and interpretable to scientists with other domain expertise. Why Absci’s AI team? Absci offers AI Scientists a unique opportunity to not only develop novel, cutting edge machine learning models, but also apply these models in real-time to generate candidate antibody therapeutics. In particular: Absci provides its AI Scientists with access to industry-leading compute resources, enabling large-scale experimentation for model training and deployment. Absci maintains its own Wet Lab, enabling AI Scientists to validate novel modeling methods via both in silico and in vitro experimentation. Absci maintains and is growing its own internal pipeline of assets, enabling AI Scientists to see their work directly translated into therapeutic impact for patients. This position can be remote, hybrid, or onsite in New York, NY or Vancouver, WA. Key Responsibilities Develop state-of-the-art deep learning models for structure-based antibody design, antibody sequence design, antibody-antigen co-folding, antibody-antigen binding prediction, and physics-based antibody design and evaluation Partner with teammates in AI Research, Platform Engineering, and Computational Biology to identify key challenges and design innovative, AI-driven solutions Analyze in silico and in vitro validation results to iteratively improve design and evaluation methodologies Deliver and publish high-impact research that advances Absci’s position as a thought leader in the field of AI antibody design Qualifications Compensation and Benefits The base salary range for this position is $160,000- $260,000. The range provided is based on what we believe is a reasonable estimate for the base salary range for this job at the time of posting. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law. Absci offers highly competitive salaries and benefits including medical, dental, and vision insurance, unlimited vacation, parental leave, employee assistance programs, voluntary life and disability insurance, annual bonus potential, the ability to participate in our employee stock purchase plan, a 401(k) with a generous company match, and so much more. Legal authorization to work in the United States is required. Absci is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, sexual orientation, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, marital status, or any characteristic protected under applicable law. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should request the recruiter or hiring manager or contact hiring@absci.com.

• Design and implement a lightweight supervised fine tuning training pipeline using open source LLMs. • Create new benchmarks to evaluate frontier models across defined scientific and performance criteria. • Analyze production models to identify measurable areas for improvement. • Improve model performance through targeted retraining and hyperparameter search. • Deploy improved models while maintaining core model characteristics and avoiding regression. • Build Python tooling to automate training, evaluation, benchmarking, and experimentation workflows. • Implement structured evaluation methods, including rubric based scoring and LLM as a judge workflows. • Document experimental design, benchmark methodology, and performance results with clarity and precision. • Iterate rapidly in a research driven environment to increase model quality and reliability.

• Conduct applied research related to AI model evaluation, data quality, and validation methodologies • Co-author research papers, technical reports, and whitepapers • Implement research prototypes and experimental systems • Support internal R&D initiatives in areas such as Agentic AI systems, LLM evaluation and validation, Speech and multimodal model assessment, Data-centric AI methodologies • Collaborate with the engineering team to translate research ideas into practical workflows • Develop experimental code and proof-of-concept implementations • Work with datasets used for training, evaluation, and benchmarking • Design experiments and analyze results • Write technical blog articles explaining recent advances in AI and ML • Translate complex research topics into accessible technical content • Support marketing and communications teams with technically accurate material • Contribute educational materials and technical explainers • Attend academic and industry conferences • Engage with researchers from AI companies and academia • Discuss research topics, evaluation challenges, and data requirements • Identify opportunities for collaboration related to dataset needs and model evaluation • Maintain professional follow-up communication after conferences