Senior Machine Learning Engineer

Reposted 16 Days Ago
Easy Apply
Hiring Remotely in US
Remote
Senior level
Machine Learning • Software
The Role
The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.
Summary Generated by Built In

Vectara provides a scalable platform to deploy your Enterprise AI Agents and AI Assistants with Accuracy, Security, and Explainability like no other solution. Our enterprise RAG Platform offers unparalleled Accuracy, Security, and Explainability by leveraging the strongest models for retrieval, embedding, reranking, an optimized LLM trained for quality, and advanced Hallucination Mitigation. We are the developers of the Hughes Hallucination Evaluation Model and Correction model, core to ensuring accuracy, quality, and responsible AI that is production-ready. These innovations have been cited in the New York Times, Visual Capitalist, and many other leading publications. This platform has allowed us to be very successful with over 100 Enterprise clients, including the likes of large US military organizations, Financial services, Healthcare, and Manufacturing.

Our founding team includes industry veterans and experts in neural information retrieval and distributed systems from Google. Join us as we pursue our mission to help the world find meaning. People at Vectara are passionate about ensuring customers take advantage of breakthroughs in applied Artificial Intelligence (AI) to solve real-world technology and business problems today. Our team is a group of unquestionable all-stars in their respective fields of computer science and business from Google, Cloudera, Splunk, MongoDB, Elastic, and more.

Equity and Salary Range: 

Salary is just one component of Vectara’s employee compensation. Our full-time employees are also equity owners in the company, which although not an immediate cash component, can have positive impacts on long-term total compensation for each participating employee. We would be remiss if we didn’t highlight and celebrate our focus on engaging many of our employees in being economic co-owners of the business.

Job responsibilities

  • Design, prototype, research and build AI systems for Vectara.
  • Train, evaluate and deploy ML models in the domains of Natural Language Processing, Information Retrieval, AI Agents, Large Language Models (LLMs) and Multimodal Large Language Model (MMLLMs).
  • Improve the quality of Vectara’s AI Agents and RAG-as-a-service platform, working on features like agentic behavior, hallucination reduction/correction, and agent orchestration.
  • Publish technical blogs, papers, and patents.

Basic requirements

  • BS/MS in Computer Science, Statistics, Electrical/Computer Engineering, Mathematics, or a related field. 
  • 8+/7+ years of professional work experience after BS/MS applying machine learning to real-world problems, and crafting scalable and effective ML/AI solutions.
  • Strong domain knowledge in at least one of the following: RAG, LLM, information retrieval, Multimodal LLMs.
  • Excellent programming skills in Python. Proficiency in data/ML libraries such as pandas, transformers, and torch.
  • Familiarity with the technical details of deep learning concepts, such as Transformers, Retrieval-Augmented Generation (RAG), mixture of experts (MoE).
  • Hands-on experience in training ML systems end-to-end from data curation to evaluation and deployment.

Preferred Requirements

  • PhD in Computer Science/Engineering with 3+ years of industry experience.
  • Publications in prestigious venues such as ACL, NAACL, EMNLP, NeurIPS, ICML, ICLR as a key author.
  • Experience as an ML engineer in an early-stage, high growth environment.
  • Expertise in the following areas:
    • Embedding models, rerankers
    • Multimodal retrieval, question answering, and reasoning
    • Vector databases, BM25
    • Planning and reasoning in LLMs
    • Multilinguality in LLMs
    • NLG Evaluation such as hallucination detection

Equity and Salary Range: 

Salary is just one component of Vectara’s employee compensation. Our full-time employees are also equity owners in the company, which although not an immediate cash component, can have positive impacts on long-term total compensation for each participating employee. We would be remiss if we didn’t highlight and celebrate our focus on engaging many of our employees in being economic co-owners of the business.

Vectara welcomes all. We value the collective wisdom of people from different backgrounds, experiences, abilities and perspectives.  We never discriminate on the basis of race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. Vectara has a positive and supportive culture—we look for people who are inventive and work to be a little better every single day. We seek to be smart, humble, hardworking and, above all, curious. After all, we are on a mission to find meaning.  

Perks and Benefits:

100% paid Medical, Dental, Vision begins on your first day! Option of Health Savings Account (HSA) or Flexible Savings Account (FSA). Generous paid time off (PTO) plus paid sick time, holidays, and company rest days. Professional development and training opportunities. Company virtual happy hours and fun team building activities and more. 

Top Skills

Deep Learning
Machine Learning
Natural Language Processing
Pandas
Python
PyTorch
Retrieval-Augmented Generation
Transformers
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The Company
Palo Alto, CA
31 Employees
Year Founded: 2022

What We Do

Vectara is an LLM-powered Answer as a Service. The platform provides a #chatgpt like service which enables you to have a conversation with your own data. Our 100% neural natural language understanding (NLU) technology provides radical increases in semantic relevance. Instead of a list of results ala legacy keyword-based systems, we provide a direct answer to the user's input prompt. Vectara’s complete neural pipeline is available as a service through an API-first platform that allows developers to easily add semantic answer serving within their applications.

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