Senior Machine Learning Engineer
Cresta is hiring a Senior Machine Learning Engineer for a remote role open to applicants in Canada. Level rates it ; you can apply on Cresta.
Level's read on this job
- Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include Hugging Face, Vertex AI and PyTorch.
- Level classifies it as a senior role.
- Level lists 86 other open roles at Cresta.
AI in this role
Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day.
Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu, founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.
Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future 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.
Our use of AI in recruiting: We may use AI tools in our recruiting process, which require human review and oversight. If you have questions about our use of AI or wish to opt out, please contact recruiting@cresta.ai (if you are opting out, please use the subject ‘Opt-Out’ in your email).
Recording & AI transcription: We do not authorize candidates to record or use AI transcription of any interview by phone, notetaker app, AI glasses, or other device. Candidates may request an exception or accommodation for review during the interview process as needed.
Recruiting impersonation scams: 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.
How we rate this
Senior Machine Learning Engineer at Cresta rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $199k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What's a project where you used Hugging Face hands-on?
- Walk me through how you've used Vertex AI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, NLP, Hugging Face, and Vertex AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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