7 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
Categories
About Hop
Hop is a privately held staffing marketplace that connects AI, GenAI, and machine-learning talent from Latin America with companies worldwide. It sources, screens, and places data scientists and AI engineers using an in-house assessment platform, and complements recruiting with mentorship and training programs. Founded in 2016 and headquartered in Walnut Creek, California, Hop operates on recruiting and staffing fees for organizations building data and AI products.