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Our client, a leading Fintech company, are hiring a Staff Machine Learning Engineer to join their Applied AI team remotely. The successful candidate will be responsible for developing and deploying AI-powered multi-agent systems, human-in-the-loop co-pilots, specialized financial models and seamless legacy system integrations to automate processes, improve workflows and optimize existing financial technologies.
Responsibilities- Design and fine-tune both open source and proprietary large language models (LLMs) for tasks including summarization, reasoning, planning and question answering.
- Build and enhance advanced Retrieval Augmented Generation (RAG) pipelines featuring embedding fine-tuning, hybrid search, reranking and knowledge graph integration.
- Develop autonomous AI agent workflows that support proactive and adaptive decision-making.
- Utilize reinforcement learning methods (such as PPO, DPO, GRPO) to continuously improve model performance.
- Create evaluation frameworks and define metrics to rigorously assess model effectiveness.
- Deploy AI models into production environments with a focus on low latency, reliability and scalability.
- Work closely with product and engineering teams to deliver comprehensive AI-powered financial solutions.
Skillset- Master’s or Bachelor’s degree with at least 5 years of professional experience in applied AI/ML engineering.
- Demonstrated success in delivering generative AI products utilizing LLMs and autonomous agent workflows.
- Practical expertise with LLM fine-tuning methods (such as LoRA), inference frameworks (including vLLM) and sophisticated RAG pipelines.
- In-depth understanding of reinforcement learning fine-tuning techniques and associated frameworks.
- Early-stage startup experience is an advantage.
Benefits- Salary: $190k - $225k DOE.
- Remote working.
- Comprehensive health, dental and vision coverage.
- Retirement benefits.
