AI Researcher / Machine Learning Engineer

Vivo HealthStaff Inc.; San Juan (PR); Hybrid; USD 175,000 - 300,000; Full time

Benefits offered by this job

Health benefits

Flexible PTO

Job summary

Vivo HealthStaff Inc. seeks an AI Researcher / Machine Learning Engineer to bridge frontier AI with real-world deployments. You will define roadmaps, set engineering bar, and take ML systems from concept to scalable production.

You will ship agentic components, evaluation, and robust pipelines to move models into live environments. The role emphasizes hands-on experimentation, fast iteration, and collaboration with product teams.

Qualifications

• 1–6 years of software or ML eng. experience.
• Experience shipping ML systems from concept to production.
• Proficiency in Python and Elixir.
• Top-tier AI tool user with curiosity.
• Ownership mindset and clear communication.
• Able to move fast and learn new stacks.

Responsibilities

• Design the agentic layer for scalable AI systems.
• Implement self-checking, reflection, and verification before results reach humans or downstream systems.
• Build systems to measure model performance across stores and refine models.
• Orchestrate agentic workflows and retrieval augmented generation.
• Productionize prompt pipelines, retrieval, and light fine-tuning to impact metrics.
• Stand up low-latency inference paths with observability.
• Own vision tooling, testing infra, and test models on edge and cloud.

Skills

Python

Elixir

Production ML

Ownership mindset

Communication

Fast learner

Education

Master's in Computer Science

PhD in Computer Science/Physics/Applied Mathematics/AI

Tools

LangGraph

Job description

Job Title: AI Researcher / Machine Learning Engineer

About This Role

We are looking for a dedicated AI Researcher to join our team four our client. Unlike some positions that focus strictly on applied vision engineering and explicitly state they are not research roles, this role bridges the gap between frontier applied AI and real-world execution. Inspired by frontier applied AI labs building zero-touch enterprise solutions, you will help define our roadmap and engineering bar while working on high-leverage projects. You will be responsible for taking ML systems from concept to real-world scale.

Key Responsibilities

• Design the agentic layer.
• Implement self-checking, reflection, and verification passes before results reach humans or downstream systems.
• Build systems that measure model performance across every new store, catch when results stop meeting standards, and refine the models.
• Orchestrate agentic workflows and retrieval augmented generation.
• Productionize prompt pipelines, retrieval, and light fine-tuning, where it moves the needle.
• Stand up inference paths with low latency serving and token-level observability.
• Own vision tooling and testing infrastructure, and try out new model variants on the edge device and in the cloud.

Minimum Requirements

• 1-6 years of experience as a software or machine learning engineer.
• Has taken a CV or ML system from concept to real-world deployment, including evals, training pipelines and signal refinement.
• Experience in tech stacks including Python and Elixir.
• A top-decile AI power user who keeps exploring new tools.
• Ownership mentality, crisp communication, and comfortable making decisions with 80 percent information.
• Move fast without breaking things, not afraid to learn new stacks, bring a we will figure it out attitude.

Preferred Qualifications

• Master's in Computer Science.
• PhD in Computer Science, Physics, Applied Mathematics, Artificial Intelligence, or a related field.
• Familiarity with LangGraph is a plus.
• Open-source work or side projects are a big plus.

Compensation and Benefits

• Base salary range of $175K-$300K, with total comp including equity.
• Alternative compensation packages may offer $185K-$205K along with competitive equity.
• Top-tier health benefits and flexible PTO.

Logistics & Work Policy

• Location: We offer flexible options based on the project team, ranging from in-person 5 days a week at the San Francisco office to fully remote within the United States.
• Remote Requirements: For remote roles, you must be US-based, working at least 5 hours of overlap with Mountain Time, with one on-site per quarter.
• Visa Sponsorship: Depending on the specific role, we may be open to visa transfers (e.g. OPT, H1B transfers) and sponsorships (e.g. new H1B, TN), or the role may require a US citizen or green card holder.