Senior Machine Learning Engineer

Introduction to Demandbase:

Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandbase to maximize revenue, minimize waste, and consolidate their data and tech stacks – all in one platform.

As a company, we’re as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have also continuously been recognized as One of The Best Places To Work in the San Francisco Bay Area by Fortune, and One of The 60 Best Companies To Sell For by Selling Power. Our offices are located in San Francisco, New York, Austin, Seattle, India, and the United Kingdom.

About the Role

We are looking for a Senior Machine Learning Engineer to help architect and build next-generation Agentic AI systems at Demandbase. This role focuses on multi-agent orchestration, LLM-powered reasoning systems, evaluation frameworks, guardrails, and scalable GenAI architectures.

You will work at the intersection of advanced data science, generative AI research, and production-grade ML systems, shaping how intelligent agents operate reliably, safely, and effectively in enterprise environments.

This is not a platform infrastructure role — it is a deep AI systems engineering role centered around agent architecture, model evaluation, reasoning systems, and applied ML innovation.

Key Responsibilities

Agentic AI & Multi-Agent Architecture

• Design and implement multi-agent systems for complex enterprise workflows.

• Build agent orchestration frameworks (planner-executor, tool-using agents, retrieval-augmented agents, self-reflective agents).

• Develop architectures for reasoning loops, memory systems, tool integration, and contextual grounding.

• Design guardrails for hallucination mitigation, tool misuse prevention, and safe execution.

• Implement feedback-driven refinement loops and self-correction strategies.

GenAI Systems, Evals & Guardrails

• Design and operationalize LLM evaluation frameworks (automated evals, LLM-as-judge, human-in-the-loop, adversarial testing).

• Build robust prompt engineering and prompt versioning strategies.

• Develop safety guardrails including content filtering, policy enforcement, and bias monitoring.

• Implement quality metrics for:

• Factual accuracy

• Groundedness

• Latency and cost efficiency

• Agent reliability

• Create structured evaluation pipelines to continuously improve agent performance.

Advanced Data Science & NLP

• Apply advanced NLP techniques (transformers, embeddings, fine-tuning, RAG pipelines).

• Work deeply with unstructured and semi-structured data.

• Develop model experimentation frameworks for prompt optimization, fine-tuning, and retrieval strategies.

• Optimize data pipelines using Python, Pandas, Spark, and vector databases.

• Collaborate with data scientists to convert research prototypes into scalable AI systems.

AI System Design & Architecture

• Architect modular, extensible AI systems for long-term maintainability.

• Design retrieval-augmented generation (RAG) systems with advanced chunking, embedding strategies, and re-ranking.

• Build memory architectures (short-term, long-term, vector-based).

• Optimize inference pipelines for performance, cost, and reliability.

• Define reusable patterns for enterprise-grade AI systems.

Operational Excellence for AI Systems

• Implement evaluation-driven CI/CD for GenAI systems.

• Establish monitoring for:

• Model drift

• Agent failure modes

• Tool misuse

• Hallucination frequency

• Maintain reproducibility through experiment tracking and versioning.

• Ensure ethical AI practices and compliance with enterprise standards.

Technical Leadership & Mentorship

• Define best practices for agentic AI architecture and LLM system design.

• Mentor engineers and data scientists in advanced GenAI methodologies.

• Drive internal thought leadership in Agentic AI and applied GenAI research.

• Contribute to building a high-performing AI engineering culture.

Basic Qualifications

• 8+ years of experience in Machine Learning, AI Engineering, or Applied Data Science.

• Strong expertise in Generative AI systems and LLM architectures.

• Experience designing multi-agent or tool-using AI systems.

• Deep proficiency in Python and ML ecosystems (NumPy, Pandas, PyTorch/TensorFlow).

• Hands-on experience with:

• RAG systems

• Prompt optimization

• Evaluation frameworks

• Embedding models & vector databases

• Strong understanding of transformers, embeddings, and fine-tuning methods.

• Experience building production-grade AI systems from research to deployment.

• Strong system design and architectural problem-solving skills.

Preferred Qualifications

• MS or PhD in Computer Science, AI, ML, or related fields.

• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, custom agent frameworks).

• Experience with automated eval frameworks and benchmarking strategies.

• Familiarity with reinforcement learning, RLHF, or agent self-improvement loops.

• Experience with vector databases and retrieval systems.

• Published research or open-source contributions in AI/ML.

• Strong understanding of AI safety and responsible AI practices.

What You’ll Gain

• Opportunity to architect enterprise-scale Agentic AI systems.

• Direct impact on next-generation AI product capabilities.

• Exposure to cutting-edge developments in LLMs, multi-agent systems, and AI safety.

• A culture that values deep technical thinking, experimentation, and innovation.

• The chance to help define Demandbase’s AI future.

Benefits

Our benefits include Group Medical, Personal Accident, and Term Life Insurance for comprehensive protection. Preventive healthcare covers dental, vision, and OPD needs, complemented by strong mental health support. We also provide a fitness benefit, car lease policy, and gratuity for long-term financial well-being.

Our Commitment to Diversity, Equity, and Inclusion at Demandbase

At Demandbase, we believe in creating a workplace culture that values and celebrates diversity in all its forms. We recognize that everyone brings unique experiences, perspectives, and identities to the table, and we are committed to building a community where everyone feels valued, respected, and supported. Discrimination of any kind is not tolerated, and we strive to ensure that every individual has an equal opportunity to succeed and grow, regardless of their gender identity, sexual orientation, disability, race, ethnicity, background, marital status, genetic information, education level, veteran status, national origin, or any other protected status. We do not automatically disqualify applicants with criminal records and will consider each applicant on a case-by-case basis.

We recognize that not all candidates will have every skill or qualification listed in this job description. If you feel you have the level of experience to be successful in the role, we encourage you to apply!

We acknowledge that true diversity and inclusion requires ongoing effort, and we are committed to doing the work required to make our workplace a safe and equitable space for all. Join us in building a community where we can learn from each other, celebrate our differences, and work together.

Unsolicited Submissions

At Demandbase, we value thoughtful partnerships and direct connections with candidates. We’re not accepting unsolicited resumes or outreach from third-party recruiting agencies. Any unsolicited submissions will not be reviewed, and no fees will be paid.