Machine Learning Engineer

Mission Context We are building a causal decision engine for high-stakes systems where reasoning must be explicit, interventions must be provable, and outcomes must be accountable. What You'll Work On Implement and train machine learning and generative models, including LLM-based systems. Build and maintain data pipelines for training, evaluation, and inference. Support agent-based workflows for reasoning, simulation, and decision support. Collaborate with senior engineers and researchers to bring models into production. Debug, evaluate, and iterate on models under real performance and reliability constraints. What We Look For Hands-on experience with Python and common ML frameworks. Familiarity with LLMs, transformers, or generative models. Comfort working with data: cleaning, preprocessing, and evaluation. Curiosity, ownership, and a strong desire to learn by building. Bonus Exposure to time series data, multimodal models, or causal reasoning concepts is a plus. Work Style Impact-first: focus on building things that work. Learning-by-doing: fast feedback, real systems, real users. Ownership-minded: take responsibility for what you ship. Collaborative: learn from researchers and senior engineers. Why Join Abel Work on real-world AI systems, not toy problems. Learn directly from experienced AI researchers and engineers. Build foundations in LLMs, agents, and decision intelligence. Grow quickly in a high-ownership, low-bureaucracy environment. Apply Send your resume or profile to hiring@abel.ai with subject: [Application] ML Engineer - Your Name Back to Careers