Staff Machine Learning Engineer

Alldus International Consulting Ltd; Colorado; On-site; USD 190,000 - 225,000; Full time

Benefits offered by this job

Comprehensive health, dental and vision coverage

Retirement benefits

Remote working

Job summary

A leading Fintech company is seeking a Staff Machine Learning Engineer to join their Applied AI team remotely. The position involves developing and deploying advanced AI systems to optimize financial technologies, with a strong focus on large language models and autonomous agent workflows.

Qualifications

• At least 5 years of professional experience in applied AI/ML engineering.
• Success delivering generative AI products utilizing LLMs and workflows.
• Understanding of reinforcement learning fine-tuning techniques.

Responsibilities

• Design and fine-tune large language models for various AI tasks.
• Build advanced RAG pipelines and develop autonomous AI workflows.
• Deploy AI models with a focus on low latency, reliability, and scalability.

Skills

Applied AI/ML engineering

Generative AI products

LLM fine-tuning

Reinforcement learning

Education

Master's or Bachelor's degree

Tools

LLM fine-tuning methods

Inference frameworks

RAG pipelines

Job description

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.

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