Senior Machine Learning Engineer

at Cresta · Vertical AI · AB, Canada, Canada · Remote · Engineering

Senior Machine Learning Engineer role focused on building and scaling next-generation agentic AI systems and evaluation frameworks for contact center applications. The role involves designing multi-step agent workflows, RAG pipelines, and optimizing LLM-powered systems for production, with a strong emphasis on improving reliability, robustness, and performance.

What you'd actually do

  1. Lead the design and development of Cresta’s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
  2. Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.
  3. Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
  4. Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
  5. Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.

Skills

Required

  • LLMs
  • Prompting techniques
  • RAG
  • Multi-agent orchestration
  • Evaluation frameworks
  • NLP
  • Generative AI
  • Transformer architectures
  • Embeddings
  • Retrieval systems
  • PyTorch
  • TensorFlow
  • Hugging Face
  • Distributed/cloud-based infrastructure
  • ML system optimization
  • Technical leadership

Nice to have

  • Master’s or Ph.D.

What the JD emphasized

  • strong pre-LLM ML foundations
  • deep expertise in LLMs
  • proven ability to translate cutting-edge research into scalable, production-grade systems
  • design evaluation frameworks
  • diagnosing and mitigating failure modes
  • defining measurable quality metrics
  • architect and scale LLM and retrieval-augmented generation pipelines
  • ground models in enterprise data
  • building high-performance ML systems
  • extract structured insights
  • deliver real-time, actionable intelligence at scale
  • multi-step agent workflows
  • knowledge retrieval
  • reasoning
  • summarization
  • automated actions
  • cohesive production systems
  • Retrieval-Augmented Generation (RAG) pipelines
  • multi-agent orchestration
  • domain-adapted models
  • reasoning, planning, and tool-use capabilities
  • real-world AI applications
  • evaluation strategies for complex, non-deterministic systems
  • offline benchmarking
  • online experimentation
  • LLM-as-a-judge methodologies
  • hallucinations
  • retrieval errors
  • tool misuse
  • prompt brittleness
  • multi-step reasoning breakdowns
  • accuracy
  • faithfulness
  • task completion
  • latency
  • cost
  • robustness
  • scalability
  • latency
  • security
  • cost efficiency
  • production environments
  • Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or Ph.D. preferred.
  • 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
  • Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
  • Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
  • Experience building and evaluating complex agentic or multi-step LLM workflows.
  • Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.
  • Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Other signals

  • LLM
  • Agentic AI
  • RAG
  • Evaluation Frameworks
  • Production Systems
Read full job description

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman isSebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO,Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform,and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include:

  • Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.
  • Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.
  • Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities:

  • Lead the design and development of Cresta’s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
  • Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.
  • Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
  • Improve reasoning, planning, and tool-use capabilities in real-world AI applications.
  • Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
  • Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.
  • Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.
  • Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.
  • Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta’s platform.
  • Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s AI systems.

Qualifications We Value:

  • Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or Ph.D. preferred.
  • 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
  • Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
  • Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
  • Experience building and evaluating complex agentic or multi-step LLM workflows.
  • Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.
  • Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Perks & Benefits:

  • We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
  • Paid parental leave to support you and your family
  • Monthly Health & Wellness allowance
  • Work from home office stipend to help you succeed in a remote environment
  • Lunch reimbursement for in-office employees
  • PTO: 3 weeks in Canada

Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details.

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai