Responsibilities
- Architect and maintain scalable, reusable AI platforms and tools that support the entire AI lifecycle, including data ingestion, model training or fine-tuning, evaluation, deployment, and monitoring for both traditional and generative AI models.
- Build standardized, production-ready AI workflows and templates using tools like Airflow and MLflow to enable rapid experimentation and deployment
- Implement robust CI/CD pipelines, Docker containerization, model registries, and experiment tracking to support reproducibility, scalability, and governance in ML and genAI
- Optimize genAI technologies, including transformers, embeddings, vector databases, and real-time retrieval-augmented generation (RAG) systems
- Automate and streamline ML and genAI model training, inference, deployment, and versioning workflows, ensuring consistency, reliability, and adherence to industry best practices
- Ensure reliability, observability, and scalability of production ML and genAI workloads by implementing comprehensive monitoring, alerting, and continuous performance evaluation
- Integrate infrastructure components such as Kubernetes orchestration, Ray and cloud solutions (AWS/Azure) for robust production environments
- Drive infrastructure optimization for generative AI use-cases, including efficient inference techniques (batching, caching, quantization), fine-tuning, prompt management, and model updates at scale
- Partner with data engineering, product, infrastructure, and other stakeholder teams to align AI platform initiatives with broader company goals, infrastructure strategy, and innovation roadmap
- Contribute actively to internal documentation, onboarding, and training programs, promoting platform adoption and continuous improvement
Qualifications
- Software engineering background with experience in building distributed systems or platforms designed for machine learning and AI workloads
- Expert-level proficiency in Python and familiarity with ML frameworks (TensorFlow, PyTorch), infrastructure tooling (MLflow, Kubeflow, Ray), and popular APIs (Hugging Face, OpenAI, LangChain)
- Experience implementing modern MLOps practices, including model lifecycle management, CI/CD, Docker, Kubernetes, model registries, and infrastructure-as-code tools (Terraform, Helm)
- Demonstrated experience working with cloud infrastructure, ideally AWS or GCP, including Kubernetes clusters (GKE/EKS), serverless architectures, and managed ML services (e.g., Vertex AI, SageMaker)
- Proven experience with generative AI technologies: transformers, embeddings, prompt engineering strategies, fine-tuning vs. prompt-tuning, vector databases, and retrieval-augmented generation (RAG) systems
- Experience designing and maintaining real-time inference pipelines, including integrations with feature stores, streaming data platforms (Kafka, Kinesis), and observability platforms
- Familiarity with SQL and data warehouse modeling; capable of managing complex data queries, joins, aggregations, and transformations
- Solid understanding of ML monitoring, including identifying model drift, decay, latency optimization, cost management, and scaling API-based genAI applications efficiently
Perks and Benefits @ Clari
- Flexible working hours and hybrid work opportunities
- Life and accidental coverage
- Mental health support provided by Silver Oak Health
- Pre-IPO stock options
- Well-being and professional development stipends
- 100% paid parental leave
- Discretionary paid time off, monthly ‘take a break’ days, and Focus Fridays
- Focus on culture: Charitable giving match, plus in-person and virtual events
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What We Do
Clari's market-leading Revenue Platform helps go-to-market teams of every size and stripe take control of their entire sales process and revenue operation. With Clari’s Revenue Platform, all revenue-critical employees now have an enterprise system to run revenue. Forecasting, pipeline management, conversation intelligence, deal execution, coaching, and buyer collaboration (to name a few) are a maze of challenges made simple with Clari. Thousands of teams at leading companies worldwide, including Okta, Adobe, Workday, and Zoom use Clari to drive revenue accuracy and precision.
Why Work With Us
You’ll often hear our CEO talk about being remarkable. To Clari, remarkable means many things. We believe in providing interesting and meaningful work in a nurturing and inclusive environment. Efforts have to be recognized. Voices have to be heard. And work-life balance has to be baked into the very fiber of the company. We’d love to have you!
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