Full Stack AI/ML Developer – Digital Products

Posted 1hrs ago

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Job Description

Full Stack AI/ML Developer building AI-enabled digital products for RTX, a global aerospace and defense company. Designing cloud-native data platforms, applications, APIs, and ML integrations.

Responsibilities:

  • Collaborate with cross-functional agile teams to design, build, and manage digital products from concept through launch and adoption
  • Develop front-end architectures and intuitive, responsive user interfaces
  • Leverage Palantir Foundry for data integration, ontology management, pipeline development, operational workflows, and deployment of data-driven applications and AI/ML use cases
  • Design and implement backend services using C#, Java, and Python
  • Build and maintain scalable APIs, microservices, and integration frameworks
  • Integrate AI/ML models into applications, including inference pipelines, intelligent features, and model-driven user experiences
  • Build and maintain data and application pipelines supporting AI/ML functionality and model deployment
  • Collaborate on feature engineering, model testing, validation, and operationalization
  • Apply DevOps practices across CI/CD, automated testing, cloud deployment, and containerized workloads
  • Influence stakeholders and support decision-making through clear communication, structured artifacts, and product storytelling
  • Participate in Agile workflows including sprint definition, backlog prioritization, and iterative product releases
  • Stay current on emerging cloud platforms, AI/ML frameworks, front-end and backend tools, and modern development practices
  • Ensure solutions meet technical requirements and customer needs
  • Support UI/UX design standards and best practices

Requirements:

  • U.S. citizenship is required; only U.S. citizens are authorized to access information under this program/contract
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related technical field with 12+ years of applicable work experience; OR an Advanced Degree with 10+ years of applicable work experience
  • 10+ years of experience in data engineering, data architecture, analytics, AI/ML, or related technical domains
  • 5+ years architecting cloud-native data platforms using Azure, AWS, or GCP
  • Deep experience with Databricks, Lakehouse architectures, and modern ELT/ETL tooling
  • Strong understanding of distributed systems, real-time data streaming, data governance, and API/Integration architectures
  • Hands-on experience with Palantir Foundry, including data pipeline transformations, ontology management, and application deployment
  • Ability to design and implement enterprise-scale data architecture solutions
  • Familiarity with MLflow, PyTorch, TensorFlow, Azure ML, SageMaker, and Vertex
  • Experience with Java and Spring Boot preferred
  • Experience developing microservices and REST APIs preferred
  • Proficiency with CI/CD practices and production deployment preferred
  • Experience with Agile software delivery and SDLC management preferred
  • Experience with Docker, Kubernetes, and container orchestration platforms preferred
  • Familiarity with web application security concepts preferred
  • Experience with Apache Kafka and Kafka Streams preferred
  • Experience building or supporting AI/ML features, inference APIs, or application-level ML workflows preferred
  • Ability to explain technical concepts to engineering and non-technical stakeholders preferred
  • Strong interpersonal, problem-solving, and attention-to-detail skills preferred
  • Ability to thrive in a fast-paced environment with autonomy and accountability preferred
  • Proven ability to drive modernization, cloud migration, or digital transformation initiatives preferred

Benefits:

  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Life insurance
  • Short-term disability
  • Long-term disability
  • 401(k) match
  • Flexible spending accounts
  • Flexible work schedules
  • Employee assistance program
  • Employee Scholar Program
  • Parental leave
  • Paid time off
  • Holidays
  • Annual short-term and/or long-term incentive compensation programs may be available
  • Employee referral award may be available, subject to eligibility requirements