Staff Machine Learning Engineer

Alldus; Colorado Springs (CO); On-site; USD 200,000 - 275,000; Full time

Benefits offered by this job

Comprehensive benefits package

Job summary

Alldus, on behalf of a growing FinTech client, is hiring a Staff Machine Learning Engineer to join their Colorado team. You will design and build production-grade, multi-agent AI systems powering advisor copilots, investment intelligence, workflow automation and autonomous research.

You will lead development across Python, cloud platforms (AWS/Azure/GCP) and modern AI frameworks, focusing on scalability, observability, and fault tolerance.

Qualifications

• 6+ years of experience in Machine Learning.
• 2-3 years building and deploying Generative AI or LLM-powered applications in production.
• Proven experience designing, developing and implementing production-ready multi-agent AI systems.
• Strong expertise in multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine-tuning and synthetic data generation.
• Advanced Python programming with experience in modern AI/ML frameworks.

Responsibilities

• Design, develop and deploy production-grade multi-agent AI systems using modern agent frameworks and LLMs.
• Build intelligent AI workflows that combine context retrieval, reasoning, tool execution, validation and compliance controls.
• Develop scalable distributed services for agent orchestration with observability, monitoring, resilience and fault tolerance.
• Create evaluation frameworks to assess reasoning quality, accuracy, groundedness and numerical correctness.
• Collaborate with Product, Design and Engineering to translate business requirements into scalable AI solutions.
• Continuously optimize AI systems for performance, latency, reliability, scalability and cost efficiency.
• Influence AI infrastructure design, including model serving, orchestration, vector databases, caching and cloud-native architecture.

Skills

Machine Learning

Generative AI

Multi-agent systems

Python

Distributed systems

Cloud platforms

LLMs

Job description

Our client, a growing FinTech company, are hiring a Staff Machine Learning Engineer to join their team in Colorado. The successful candidate will play a key role in designing and building production-grade, multi-agent AI systems that power advisor copilots, investment intelligence, workflow automation and autonomous research.

Responsibilities

• Design, develop and deploy production-grade multi-agent AI systems using modern agent frameworks and large language models (LLMs).
• Build intelligent AI workflows that combine context retrieval, reasoning, tool execution, validation and compliance controls.
• Develop scalable distributed services for agent orchestration, with a focus on observability, monitoring, resilience and fault tolerance.
• Create evaluation frameworks to assess reasoning quality, accuracy, groundedness, hallucination mitigation and financial correctness.
• Implement scalable approaches to memory management, context handling and persistent agent state.
• Collaborate closely with Product, Design and Engineering teams to translate business requirements into scalable AI solutions.
• Continuously optimize AI systems for performance, latency, reliability, scalability and cost efficiency.
• Influence the design and evolution of AI infrastructure, including model serving, orchestration, vector databases, caching and cloud-native architecture.

Skillset

• At least 6 years of experience in Machine Learning, including 2-3 years building and deploying Generative AI or LLM-powered applications in production environments.
• Proven experience designing, developing and implementing production-ready multi-agent AI systems.
• Strong expertise in multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine‑tuning, agent memory and synthetic data generation.
• Advanced Python programming skills with hands‑on experience using modern AI and machine learning frameworks.
• Experience building distributed systems and deploying cloud‑native applications across AWS, Azure or Google Cloud Platform (GCP).
• Strong understanding of AI system monitoring, evaluation frameworks, reliability engineering and model performance optimization.
• Demonstrated ability to design scalable, enterprise‑grade AI architectures that integrate multiple models, services, and workflows.
• Previous experience working in a fast‑paced startup or scale‑up environment is highly desirable.

Benefits

Salary: $200k - $275k

Comprehensive benefits package.