ML Engineer, Agentic Systems

About the Team

We work together to Build high-impact tools and platforms that drive innovation – from scientific seismic algorithms to data visualization tools to intuitive web apps. combining our expertise across regions to drive innovation and impactful results. Our team values collaboration, continuous learning, and innovation, and we take pride in supporting each other to achieve shared goals.

Key Responsibilities

• Shape the application logic and user experience: define what a good result looks like, remove what does not help users decide, and make outputs easy to verify.
• Design agent workflows with branches, loops, sub-workflows, and explicit routing, choosing the simplest structure that solves the problem.
• Implement human-in-the-loop approvals, and decide which actions an agent may take on its own.
• Give agents the right context: tool-based search over files, logs, code, and databases, using text search, SQL, and semantic retrieval where appropriate.
• Ground answers in cited evidence, enforce tool permissions, and guard against prompt injection and unsafe actions.
• Integrate tools and external APIs. Handle concurrency, retries, and error paths.
• Add database-backed persistence. Ensure workflows can pause and resume reliably.
• Design and execute LLM fine-tuning strategies when needed: data curation, supervised fine-tuning with parameter-efficient methods such as LoRA, preference optimization (e.g., DPO), reinforcement learning methods such as GRPO with verifiable rewards, evaluation sets, and rollback criteria.
• Instrument agent runs with tracing and continuous evaluation, making decisions and actions auditable and detecting quality regressions early.
• Deliver production-ready services with automated tests and CI/CD, and expose APIs where other teams or systems need them.
• Collaborate with domain experts, product, and engineering. Present clear design docs and trade-offs.
• Leverage AI coding agents such as Claude Code or Codex effectively and responsibly: plan and direct their work, review and test what they produce, and stay accountable for every change that ships.

Qualifications:

Required:

• Bachelor’s degree or higher in Computer Science, Engineering, Physics, Mathematics, Geophysics, or a related field.
• Strong academic performance, including a minimum cumulative GPA of 3.5 on a 4.0 scale for all earned degrees. Equivalent academic grading systems will be considered for degrees obtained outside the U.S.
• Strong programming and software engineering fundamentals, including asynchronous and concurrent programming.
• Sound design and product judgment: you can explain why a system is built the way it is, what was left out, and how its quality is measured.
• Hands-on experience building multi-agent or graph-based LLM workflows, using established frameworks or custom implementations.
• Experience designing how agents find information: tool-based search over files, logs, and databases, and semantic retrieval with reranking when needed.
• Practical LLM fine-tuning experience: parameter-efficient methods such as LoRA, dataset preparation and quality assurance, offline and online evals; a working understanding of RL-based fine-tuning and reward design.
• Experience with tracing and evaluation of LLM applications.
• Experience building web services and APIs (e.g., FastAPI), and working with PostgreSQL, Docker, and Git.
• Ability to harness AI coding agents such as Claude Code or Codex: understand how they work, break down tasks, guide their execution, critically review their output, recognize failures, and take ownership of the resulting code.

Preferred:

• Experience designing complex agent systems, including task decomposition, parallel execution, result aggregation, and human-in-the-loop orchestration.
• Hands-on experience with LLM post-training techniques (e.g., DPO, GRPO), including reward design for verifiable outcomes and multi-step tool use.
• Experience running enterprise-scale applications in production, including retries, idempotency, timeouts, and rate limits.
• Prior work in workflow automation; exposure to geoscience or scientific computing is a plus.
• Frontend experience building lightweight operator dashboards.

Houston Benefits:

• 401k Retirement Plan - when you contribute up to 5%, not only will we match that, but we will also add an additional 2%
• Free on-site fitness centre offering group exercise classes
• Short-term disability and long-term disability coverage at no cost to you
• Parental Leave Program allowing mothers and fathers to take time off from work for childbirth, adoption and to bond with your new child
• Pet Insurance – options to meet every budget
• Wellness Program – resources provided to support your personal wellness and participation in activities can earn you $65 quarterly.

Our Hiring Process

At Viridien, we are committed to delivering a respectful, inclusive, and transparent recruitment experience.

Due to the high volume of applications we receive, we may not be able to provide individual feedback to every applicant. Only candidates whose qualifications closely match the role criteria will be contacted for an interview. We do, however, aim to share personalized feedback with those who progress to the first round of interviews and beyond.

We are also dedicated to ensuring that our hiring process accessible to all. If you require any reasonable adjustments to fully participate in the application or interview stages, please don’t hesitate to contact your recruiter directly.

We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.