5 months ago
Responsibilities
- Design, prototype, and build GenAI solutions, RAG document pipelines, and task-specific agents.
- Orchestrate multi-step agent workflows integrating LLM prompts, external APIs, and human-in-the-loop escalations.
- Own the ML lifecycle from requirements and data preparation through feature engineering, model fine-tuning, evaluation, registry management, and quality monitoring.
- Architect data ingestion, object-store lake, embedding, vector database, governance, and access-control systems.
- Deploy and operate AI systems using containers, Kubernetes, GPU scheduling, autoscaling, blue-green rollouts, cost telemetry, and automated CI/CD.
- Implement observability, structured logging, A/B and shadow testing, security controls, privacy protections, and cost guardrails.
- Translate ambiguous business ideas into roadmaps, lead build-versus-buy analysis, establish coding standards, and mentor peers on agentic patterns and ethical AI.
Requirements
- Bachelor’s or master’s degree in Computer Science, Data Science, or equivalent experience.
- 7+ years of experience designing and shipping ML/AI applications, including 2+ years with LLMs or Generative AI.
- Production experience delivering RAG or agentic systems using tools such as LangChain, LlamaIndex, n8n, or custom implementations.
- Expert-level Python and SQL skills, plus strong Spark, distributed data-processing, and performance-tuning experience.
- Hands-on experience fine-tuning foundation models and working with MLflow, Ray/KubeRay, and vector databases.
- Experience with BigQuery, Redshift, Parquet, Avro, and streaming or ingestion tools such as Airbyte and Kafka/Pub-Sub.
- Production experience with Docker, Kubernetes, Helm, and Git-based CI/CD pipelines.
- Ability to gather requirements, set technical direction, communicate clearly, and influence cross-functional teams.
- Open only to U.S. Citizens or Green Card holders.
Benefits
- The role is in-office in West Hollywood, Los Angeles.
- Compensation includes a strong base salary and bonus, with no equity because the company is private.
Tech Stack
AirbyteAmazon RedshiftApache KafkaApache SparkDockerGitHub ActionsGoogle BigQueryGrafanaHelmKubernetesMLflowPrometheusPythonSQL
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