Note: The job is a remote job and is open to candidates in USA. RealPage, Inc. is seeking a Data Scientist to help design, build, and deploy machine learning and generative AI solutions. The role involves working on production AI systems, partnering with engineering and product teams, and leading data science initiatives from concept to deployment.
Responsibilities
- Develop, evaluate, and deploy predictive and generative models for real production use cases
- Perform feature engineering and data preparation for modeling workflows
- Translate business and product questions into analytical solutions
- Build and maintain LLM powered features and services
- Develop retrieval augmented generation (RAG) pipelines using embeddings and vector databases
- Integrate LLMs with APIs and internal tools using structured function calling
- Finetune foundation models with parameter efficient approaches (e.g., LoRA)
- Evaluate model quality, detect hallucinations, and implement safety guardrails
- Use synthetic data to improve model performance, testing, and fairness
- Optimize inference performance and cost across different model providers
- Deploy and operate machine learning and GenAI models in production
- Build CI/CD pipelines for models and data workflows
- Monitor performance, data quality, and model drift
- Design versioning, rollback, and retraining strategies
- Partner with platform and infrastructure teams to ensure reliability and scalability
- Build low latency data pipelines and real time decisioning systems
- Work with streaming data and event driven architectures
- Support systems with strict uptime and response time requirements
- Contribute to feature stores used for both real time and batch inference
Skills
- 3–6 years of experience in data science, machine learning, or applied AI
- A degree (Master's or better preferred) in Computer Science, Data Science or related fields
- Strong Python and SQL skills
- Handson experience deploying models into production
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Experience with modern ML frameworks (PyTorch, TensorFlow, scikitlearn)
- Exposure to LLMs, embeddings, and GenAI workflows
- Ability to communicate clearly with engineers, product managers, and nontechnical partners
- Experience with streaming data systems
- Experience operating models at scale
- Knowledge of MLOps tools and observability practices
- Experience building AI solutions that support customer facing products
Benefits
- Certain roles are eligible for additional rewards, including annual bonus, and sales incentives depending on the terms of the applicable plan and role as well as individual performance.
Company Overview
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