Machine Learning Engineer, vLLM Inference - Tool Calling and Structured Output

Red Hat, Inc.; Toronto; On-site; CAD 185,000 - 306,000; Full time

Job summary

A leading open-source software company in Toronto is seeking a Machine Learning Engineer to innovate with vLLM systems. You will develop and maintain subsystems, ensuring efficient model performance and compliance. The ideal candidate has significant experience with Python, a strong grasp of LLM Inference concepts, and excellent communication skills. This position includes a competitive salary range of $133,650 - $220,680, along with comprehensive benefits and a collaborative work environment.

Benefits

Comprehensive medical, dental, and vision coverage

401(k) retirement plan with employer match

Paid time off and holidays

Paid parental leave

Employee stock purchase plan

Qualifications

• Strong experience in Python and Pydantic.
• Understanding of logits processing, logit generation, sampling, and decoding.
• Familiarity with libraries like Outlines, XGrammar, Guidance, or Llama.cpp.

Responsibilities

• Write robust Python and Pydantic for vLLM systems.
• Design and develop function calling and structured output subsystems.
• Participate in technical design discussions.

Skills

Python

Pydantic

LLM Inference Core Concepts

OpenAI Chat Completions API

Incremental parsing techniques

Jinja2 chat templates

Beam Search

Greedy Decoding

Tensor math libraries

Strong communication skills

Education

BS in computer science, computer engineering or related field

MS or PhD in ML-related domain

Job description

About the Job

At Red Hat, we believe the future of AI is open, and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise. The Red Hat Inference team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading contributors and maintainers of the vLLM and LLM-D projects and inventors of state‑of‑the‑art techniques for model quantization and sparsification, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments.

As a Machine Learning Engineer focused on vLLM, you will be at the forefront of innovation, collaborating with our team to tackle the most pressing challenges in model performance and efficiency. In this role, you will build and maintain subsystems that allow vLLM to speak the language of tools. You will bridge the gap between probabilistic token generation and deterministic schema compliance, working directly on tool parsers (https://docs.vllm.ai/en/v0.10.1/features/tool_calling.html) to interpret raw model outputs and structured output (https://docs.vllm.ai/en/v0.10.1/features/structured_outputs.html) engines to guide generation at the logit level. If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning in the open source way, this is the role for you.

Join us in shaping the future of AI Inference!

What You Will Do

• Write robust Python and Pydantic, working on vLLM systems, high performance machinelearning primitives, performance analysis and modeling, and numerical methods
• Contribute to the design, development, and testing of function calling, tool calling parser, and structured output subsystems in vLLM
• Participate in technical design discussions and provide innovative solutions to complex problems
• Give thoughtful and prompt code reviews
• Mentor and guide other engineers and foster a culture of continuous learning and innovation

What You Will Bring

• Strong experience in Python and Pydantic
• Strong understanding of LLM Inference Core Concepts, such as logits processing (ie. Logit Generation > Sampling > Decoding loop)
• Deep familiarity with the OpenAI Chat Completions API specification
• Deep familiarity with libraries like Outlines, XGrammar, Guidance, or Llama.cpp grammars
• Proficiency with efficient parsing techniques (e.g., incremental parsing) is a strong plus
• Proficiency with Jinja2 chat templates
• Familiarity with Beam Search and Greedy Decoding in the context of constraints
• Familiarity with LLM inference metrics and tradeoffs
• Experience with tensor math libraries such as PyTorch is a strong plus
• Strong communication skills with both technical and non-technical team members
• BS, or MS in computer science or computer engineering, mathematics, or a related field; PhD in an ML-related domain is considered a plus

The salary range for this position is $133,650.00 - $220,680.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

About Red Hat

Red Hat (https://www.redhat.com/) is the world’s leading provider of enterprise open source (https://www.redhat.com/en/about/open-source) software solutions, using a community‑powered approach to deliver high‑performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in‑office, to office‑flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We’re a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits

• Comprehensive medical, dental, and vision coverage
• Flexible Spending Account – healthcare and dependent care
• Health Savings Account – high deductible medical plan
• Retirement 401(k) with employer match
• Paid time off and holidays
• Paid parental leave plans for all new parents
• Leave benefits including disability, paid family medical leave, and paid military leave
• Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Note: These benefits are only applicable to full‑time, permanent associates at Red Hat located in the United States.

Inclusion at Red Hat

Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from different backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions that compose our global village.

Equal Opportunity Policy (EEO)

Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee.

Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email application‑[e-mail].

General inquiries, such as those regarding the status of a job application, will not receive a reply.