GCP AI Platform Engineer
Role summary
OpenKyber is seeking a Machine Learning Engineer to focus on AI Safety for LLMs, including multi-lingual, multi-modal, and reasoning models. The role involves developing datasets and moderator models for evaluating LLM safety and fairness, and training LLMs using SFT and RL techniques. Responsibilities include researching bias detection and mitigation, defining key metrics for responsible AI behavior, and contributing to safety tools. The ideal candidate will have a Bachelor's or Master's degree in Computer Science or equivalent experience, with at least 2 years of experience as an ML Engineer or Deep Learning Scientist. Strong Python programming skills, experience with ML frameworks like TensorFlow or PyTorch, and proficiency in data manipulation with NumPy and pandas are essential. Familiarity with software development practices and version control systems like Git is also required. This hybrid role is based in Santa Clara, CA, with a duration of 12+ months.
Role: AI/ ML Engineer Duration: 12+ months Location: Santa Clara, CA (Hybrid 3-4 days onsite) Top 3 Skills: The 3 skill set or experience below requires Python programming expertise. Data Analytics Data Generation Strategies/SFT experience Model Fine Tuning Skills Job Overview: As a Machine Learning Engineer, you'll work alongside OpenKyber's research and engineering teams, focused on AI Safety for LLMs, including multi-lingual, multi-modal, and reasoning models. We value expertise in data science paired with a robust data engineering foundation. This role is directed at assessing and improving the safety and inclusivity of our LLM models in a scalable fashion. We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model fine-tuning. We believe in proactive problem-solving, minimal supervision, and being exceptional teammates who collaborate, think, and learn as one unit. Let's make a difference together! Responsibilities: 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. Qualification: 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.
For applications and inquiries, contact: hirings@openkyber.com