LLM & ML Engineer at Conviva

Foster City, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Jan, 26

Salary

200000.0

Posted On

18 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, LLM, AI, Big Data, NLP, MLOps, Reinforcement Learning, Model Fine-Tuning, Software Engineering, Data Analysis, Problem Solving, Communication, Statistical Analysis, Distributed Systems, Conversational AI

Industry

Software Development

Description

Conviva is the intelligence layer for digital businesses, turning every consumer interaction into outcome-based intelligence—linking engagement patterns across AI agents, apps, websites, and streaming video to real results such as purchases, bookings, and resolved support requests. Powered by its patented Time-State Technology®, the Conviva® Operational Data Platform delivers real-time insights and automation that help leading enterprises grow, improve satisfaction, and build lasting trust. As an LLM & ML Engineer, you will help shape the next generation of AI-powered analytics and customer experience solutions. You’ll work with a team of experienced engineers and researchers to design, build, and deploy AI systems that bring Large Language Model (LLM) capabilities to Conviva’s products. This is a hands-on opportunity to grow your expertise across applied AI, from model integration and evaluation to building scalable ML pipelines and intelligent features that help customers understand and optimize outcomes in real time. What Success Will Look Like: Contribute to the design, development, and maintenance of LLM/ML systems that power AI-driven features across Conviva’s analytics platform. Implement and fine-tune LLM-based solutions for specific product use cases, focusing on quality, performance, and efficiency. Support the development of scalable ML infrastructure for model training, deployment, and monitoring. Apply ML and AI techniques to real-world big-data and observability problems. Collaborate with product and engineering teams to align AI outputs with business needs and customer requirements. Write clean, maintainable code and follow software engineering best practices. Who You Are & What You've Done: Bachelor's or Master’s degree in Computer Science, Mathematics, Engineering, or a related field. Solid understanding of machine learning fundamentals, algorithms, probability, and statistics. Strong programming skills in Python and familiarity with modern software development practices. 1-3 years of hands-on experience building or supporting ML models, pipelines, or AI-powered applications (including internship or project experience). Experience with LLM agent techniques and AI system integration. Passion for machine learning technologies and enthusiasm for building cutting-edge solutions. Strong communication and problem-solving skills, with a proactive and curious mindset. Bonus Points: Experience with conversational AI and agent-based systems (e.g., MCP or A2A). Solid understanding of Natural Language Processing techniques and LLM/ML/Reinforcement Learning methodologies. Proficiency with ML frameworks such as PyTorch, TensorFlow, and MLOps tools. Background in model fine-tuning, alignment, and optimization techniques. Open-source contributions to ML/AI projects. Experience with big data frameworks (e.g., Spark, Flink, Ray) and distributed systems. *This position will be based in our Foster City, CA office. The expected salary range for this full-time position is $160,000 - $200,000 + equity + benefits. The actual level and compensation are determined by several factors, such as your qualifications, professional background, and relevant experience. To learn more about how Conviva can help improve the performance and outcomes of your digital services, visit www.conviva.com

Responsibilities

Contribute to the design, development, and maintenance of LLM/ML systems that power AI-driven features across Conviva’s analytics platform. Implement and fine-tune LLM-based solutions for specific product use cases, focusing on quality, performance, and efficiency.