Note: The job is a remote job and is open to candidates in USA. Scalence L.L.C. is seeking an experienced AI Engineer (Data Scientist) to develop AI-powered solutions advancing veterinary health care. The role focuses on designing and operationalizing machine learning, NLP, generative AI, and predictive modeling workflows using Python and Databricks to support clinical decision-making, disease risk modeling, and automated diagnostic report interpretation.
Responsibilities
- Design, prototype, and operationalize AI models using Python, Databricks, and MLflow for veterinary healthcare applications
- Apply machine learning and natural language processing (NLP) to structured and unstructured clinical data, including EMR records, diagnostic imaging, and laboratory/pathology results
- Develop predictive models for disease risk stratification, prognosis, and treatment outcome prediction
- Collaborate with veterinary subject matter experts to translate domain questions into reproducible data science workflows
- Develop explainable AI models to support clinical decision-making and trust in automated recommendations
- Contribute to the creation of quality evaluation frameworks for AI-driven tools
- Partner with data engineers to implement scalable data ingestion and processing systems on Databricks
- Utilize Claude Code for AI coding assistance
- Apply prompt engineering guidelines, strategies, and optimization techniques to improve generative model outputs
- Apply retrieval-augmented generation (RAG) and related techniques—such as context engineering, embedding-based search, and hybrid knowledge reasoning
- Participate in agile development cycles, maintaining thorough technical documentation and experiment traceability
- Use best practices for version control using Git
Skills
- Strong collaboration, communication, and documentation skills
- Proven experience working with large, distributed datasets
- Experience with data exploration, statistical analyses, and visualizations
- Strong statistical foundation with broad knowledge of deterministic and probabilistic statistical methods
- Strong background in supervised/unsupervised machine learning, or natural language processing (NLP)
- Experience with advanced Named Entity Recognition (NER) techniques to extract structured entities from text data
- Demonstrated mastery of prompt engineering methods—prompt engineering, fine-tuning, self-reflection, chain-of-thought reasoning, and declarative prompting
- Experience with Databricks platform
- Strong software development skills
- Experience using Git for version control in a collaborative team environment, including branching, pull requests, and code review
- Bachelor's in Data Science, Computer Science, Biomedical Engineering, or a related quantitative field
- 5+ years of experience developing ML/AI solutions in Python (Pandas, PySpark, scikit-learn, MLflow)
- Experience with using Claude Code for coding assistance
- Hands-on experience developing and orchestrating AI agents or agentic workflows using LLM frameworks
- Classification – decision trees, logistic regression, random forest, SVM, neural networks
- Familiarity with healthcare or life sciences datasets — electronic medical records (EMR), radiology, pathology, or epidemiological data preferred
- Knowledge of veterinary health informatics, disease taxonomy, or ontology-based data integration
- Experience with knowledge graph, semantic web or ontology development techniques
Benefits
- Remote/virtual work arrangement
Company Overview