AI Safety Engineer

Develop datasets and moderator models for evaluating LLM models and end-to-end systems for Content Safety, ML Fairness. These LLM models can be txt-to-txt or multimodal-to-txt. - Develop datasets for training LLM models with SFT and RL techniques, for Content Safety, ML Fairness, Security and more. - Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems. - Define and track key metrics for responsible LLM behavior and usage. - Follow the best practices of automation, monitoring, scale, safety. - Contribute to our repositories and develop safety tools to help ML teams be more effective. - Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets. - Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance. - Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. What we need to see:

Bachelor’s or Master’s Degree in Computer Science or related field or equivalent experience. - 2+ years of work experience as a Machine Learning Engineer or Deep Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions. - Strong programming skills in languages such as Python. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn. - Proficiency in data manipulation, analysis, and visualization using tools like NumPy and pandas. - Deep understanding of machine learning algorithms, statistical models, and data structures. - Familiarity with software development practices and version control systems (e.g., Git). - Good at problem solving and analytical ability. - Excellent collaboration and communication skills. Ways to stand out from the crowd:

Experience with GenAI Security including Prompt Injection Stability, Model Extraction, Confidentiality/Data Extraction, Integrity, Availability and Adversarial Robustness. - Experience with one or more of the following areas within Content Safety: Hate/Harassment, Sexualized, Harmful/Violent, or other specific areas from your application. - Experience with alignment/fine-tuning of LLMs - including regular LLMs as well as VLMs  (Vision Language Model) or any-to-text

Experience with multimodal and/or multilingual Content Safety, legal and regulatory compliance. - Passion for AI and a demonstrated commitment to advancing the field through innovative research, prior scientific research and publication experience. Sustainable Talent is a M/F+, disabled, and veteran equal employment opportunity and affirmative action employer.