Applied ML Engineer Jobs

Our client, an AI-driven organization in the Fintech industry, are hiring a Staff Machine Learning Engineer to join the team in Colorado. The successful candidate will will focus on building end-to-end generative AI products leveraging your deep expertise in large language models, fine-tuning techniques and reinforcement learning.


Responsibilities

• Design and build multi-agent systems that automate tasks and streamline workflows, delivering measurable operational impact.

• Develop AI co-pilots for advisors and other user personas, supporting workflows across prospecting, conversion, onboarding and client servicing.

• Create purpose-built, low-latency models for complex, multi-turn financial services interactions.

• Enable AI-driven optimisation and navigation of legacy platforms using computer-use and automation models.

• Design, fine-tune, and deploy open-source and proprietary LLMs for use cases including Q&A, summarisation, reasoning and planning.

• Build advanced Retrieval-Augmented Generation (RAG) pipelines, incorporating query rewriting, embedding fine-tuning, hybrid search, re-ranking and knowledge graphs.

• Apply reinforcement learning techniques, including RL fine-tuning methods such as PPO, DPO, and GRPO, to continuously improve model performance.

• Deploy models to production, ensuring high performance, reliability, scalability and low latency.

Skillset

• At least 5 years of experience in applied AI/ML engineering.

• Demonstrated success delivering production-grade generative AI products with large language models at their core.

• Hands-on experience with LLM fine-tuning techniques (e.g. LoRA), inference frameworks (e.g. vLLM) and advanced Retrieval-Augmented Generation (RAG) architectures.

• Strong practical expertise in reinforcement learning fine-tuning methods and supporting tooling.

• Previous experience working in an early-stage startup is a plus.

Benefits

• Salary: $170k - $220k DOE