Senior Data Scientist, Engineer

Automation Anywhere

. Build, evaluate, and deploy machine learning, deep learning, NLP, and LLM-based applications .

Posted 10/7/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning and deep learning applications, with a strong focus on LLM systems and prompt engineering. Proficient in developing scalable data pipelines and applying AI techniques to solve real-world business challenges.

Highest-signal resume keywords

Machine LearningDeep LearningNatural Language Processing (NLP)Python ProgrammingData Pipeline Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language Processing (NLP)Python ProgrammingJava ProgrammingSQLData ProcessingModel TrainingPrompt EngineeringFeature Engineering

Soft Skills

CollaborationProblem SolvingRisk ManagementContinuous Improvement

Tools & Technologies

APIsMicroservicesCloud InfrastructureVector DatabasesRetrieval-Augmented Generation (RAG)

Industry Keywords

Artificial IntelligenceData ScienceAgent-Based ArchitecturesMCP ProtocolsA2A Protocols

Tech Stack

Tools & technologies

CloudDistributed SystemsJavaMicroservicesPythonSQL

About the role

Key responsibilities & impact

Build, evaluate, and deploy machine learning, deep learning, NLP, and LLM-based applications
Develop LLM-powered agents and agentic AI systems
Design prompt engineering strategies and LLM evaluation pipelines
Implement retrieval-augmented generation (RAG) systems using vector databases and knowledge sources
Design and maintain scalable, reliable data pipelines and datasets
Perform data preprocessing, feature engineering, and model experimentation
Deploy AI/ML services via APIs, microservices, and cloud infrastructure
Monitor model performance and continuously improve system reliability and scalability
Collaborate cross-functionally to translate customer needs into technical solutions
Identify risks, manage customer pain points, and drive continuous improvement initiatives

Requirements

What you’ll need

Master’s degree in Artificial Intelligence, Computer Science, Data Science, or related field
Minimum 3-years experience in relevant fields
Strong programming skills in Python, Java, SQL and data processing
Experience working with structured and unstructured data
Knowledge of machine learning, deep learning, NLP, and LLM systems
Deep knowledge of MCP and A2A protocols
Experience with model training, evaluation, and experimentation
Familiarity with prompt engineering, agent-based architectures, and retrieval systems
Experience with APIs, distributed systems, and cloud platforms
Ability to apply data science and AI techniques to real-world business problems
Candidates should generally be authorized to work in the United States without the need for current or future sponsorship

Benefits

Comp & perks

Flexible work schedule / remote roles
Unlimited Personal Time Off
12 holidays off per year
4 days volunteer time off per year
Variety of health care and well-being benefits
Paid family/parental leave