Senior Machine Learning Engineer Agentic Workflow

Houston, MS - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

We are seeking a Senior Machine Learning Engineer / Platform Engineer to design and build a production-grade agentic workflow platform. This role sits at the intersection of LLM systems engineering distributed platforms and applied ML with a strong emphasis on orchestration reliability and extensibility. You will be responsible for architecting and implementing agent-based workflows that integrate large language models retrieval systems structured knowledge and external APIsdesigned for robustness observability and real-world business use.

Design and implement multi-agent and single-agent workflows using orchestration patterns and tools context engineering memory management and guardrail strategies.
Design RAG pipelines incorporating vector search hybrid retrieval and citation tracking.
Implement knowledge graphbacked reasoning including ontologies entity resolution and graph-based context construction.
Design evaluation frameworks for agent task completion correctness quality cost and latency.
Develop and deploy machine learning models focusing on production readiness scalability and performance.
Collaborate with data scientists to transition experimental models into robust production-grade applications.
Integrate with collaboration platforms (e.g. Teams alerting systems) for intelligent distribution of insights.
Implement and manage CI/CD pipelines to automate deployment testing and monitoring of models.
Architect and deploy systems on AWS leveraging compute storage and security services

Qualifications :

Bachelors or masters degree in computer science Engineering or related field.
6 years of experience in software engineering ML engineering or platform engineering.
Strong proficiency in writing production-grade Python and experience with Claude Code or Cursor.
Hands-on experience with LLM-based systems including:
- LangChain / LangGraph
- MCP
- Langsmith
- Claude or comparable frontier models
- AWS AgentCore or comparable agentic frameworks
Solid understanding of RAG architectures embeddings and vector search.
Experience designing and consuming APIs (REST and/or async/event-driven).
Strong cloud engineering experience on AWS.
Knowledge of how to fine-tune frontier models to specific domain knowledge
Experience with distillation quantization and small language models is a plus
Experience deploying traditional machine learning models into production environments using MLOps tools and best practices.
Knowledge of distributed systems large-scale model optimization and API development.
Exceptional ability to work on a team especially a dynamic innovative tiger team developing early stage PoC systems.
Strong understanding of container orchestration and cloud-native application design.
Ability to work in dynamic environments handling rapid experimentation and iterative development.

Additional Information :

Personal Characteristics

A self-motivated individual who thrives on seeing the results of their work and its impact on the business
Strong communication skills both verbally and in writing
A keen sense for the art of the possible
Proven ability to be flexible and work hard both independently and collaboratively
Methodical and organized - in general in experimental design and in code!
Attention to detail with strong analytical mathematical and problem-solving skills
An interest in learning about the energy commodities space
Resourceful and able to think creatively and adapt in a dynamic and energetic environment
Team player with an open non-political style and a high level of personal integrity
Desire to be a thought-partner in a fast-growing team and make an impact at a business that sits at the heart of the worlds energy flows

This Role is located in Houston TX - In office 5x a week

All your information will be kept confidential according to EEO guidelines.

Remote Work :

Employment Type :

Full-time

Design and implement multi-agent and single-agent workflows using orchestration patterns and tools context engineering memory management and guardrail strategies.
Design RAG pipelines incorporating vector search hybrid retrieval and citation tracking.
Implement knowledge graphbacked reasoning including ontologies entity resolution and graph-based context construction.
Design evaluation frameworks for agent task completion correctness quality cost and latency.
Develop and deploy machine learning models focusing on production readiness scalability and performance.
Collaborate with data scientists to transition experimental models into robust production-grade applications.
Integrate with collaboration platforms (e.g. Teams alerting systems) for intelligent distribution of insights.
Implement and manage CI/CD pipelines to automate deployment testing and monitoring of models.
Architect and deploy systems on AWS leveraging compute storage and security services

Qualifications :

Bachelors or masters degree in computer science Engineering or related field.
6 years of experience in software engineering ML engineering or platform engineering.
Strong proficiency in writing production-grade Python and experience with Claude Code or Cursor.
Hands-on experience with LLM-based systems including:
- LangChain / LangGraph
- MCP
- Langsmith
- Claude or comparable frontier models
- AWS AgentCore or comparable agentic frameworks
Solid understanding of RAG architectures embeddings and vector search.
Experience designing and consuming APIs (REST and/or async/event-driven).
Strong cloud engineering experience on AWS.
Knowledge of how to fine-tune frontier models to specific domain knowledge
Experience with distillation quantization and small language models is a plus
Experience deploying traditional machine learning models into production environments using MLOps tools and best practices.
Knowledge of distributed systems large-scale model optimization and API development.
Exceptional ability to work on a team especially a dynamic innovative tiger team developing early stage PoC systems.
Strong understanding of container orchestration and cloud-native application design.
Ability to work in dynamic environments handling rapid experimentation and iterative development.

Additional Information :

Personal Characteristics

A self-motivated individual who thrives on seeing the results of their work and its impact on the business
Strong communication skills both verbally and in writing
A keen sense for the art of the possible
Proven ability to be flexible and work hard both independently and collaboratively
Methodical and organized - in general in experimental design and in code!
Attention to detail with strong analytical mathematical and problem-solving skills
An interest in learning about the energy commodities space
Resourceful and able to think creatively and adapt in a dynamic and energetic environment
Team player with an open non-political style and a high level of personal integrity
Desire to be a thought-partner in a fast-growing team and make an impact at a business that sits at the heart of the worlds energy flows

This Role is located in Houston TX - In office 5x a week

All your information will be kept confidential according to EEO guidelines.

Remote Work :

Employment Type :

Full-time

Key Skills

Industrial Maintenance
Machining
Mechanical Knowledge
CNC
Precision Measuring Instruments
Schematics
Maintenance
Hydraulics
Plastics Injection Molding
Programmable Logic Controllers
Manufacturing
Troubleshooting

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About Company

Vitol

We are a leader in the energy sector with a presence across the spectrum; from oil through to power, renewables and carbon credits. Every day we use our expertise to distribute energy around the world. We source from producers, refiners and intermediaries and deliver to refineries, ut ... View more

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