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Principal AI Engineer 0426

nexus IT group
10 days ago
Full-time
Remote
United States
Artificial Intelligence & Machine Learning
 What You’ll Do
  • Architect and deliver scalable platform capabilities to support machine learning and AI workloads across multiple use cases
  • Partner with data scientists to translate modeling needs into performant infrastructure and production-ready systems
  • Build and manage end-to-end pipelines for data ingestion, transformation, model deployment, and monitoring
  • Establish best practices for model lifecycle management, including versioning, testing, and observability
  • Develop backend services and APIs using modern programming languages (e.g., Python, Java) and support lightweight UI integrations where needed
  • Design and optimize data storage solutions across relational, non-relational, and graph-based systems
  • Integrate platform components with messaging systems, identity providers, and external services
  • Ensure system performance, scalability, and uptime through proactive monitoring, tuning, and incident response
  • Automate operational processes to improve platform efficiency and reduce manual overhead
  • Contribute to architectural decisions around distributed systems and microservices-based environments
  • Provide technical mentorship and guidance to engineering teams leveraging the AI platform
  • Maintain clear documentation of system architecture, workflows, and operational procedures
  • Stay informed on emerging trends in AI/ML and incorporate relevant advancements into the platform strategy

What You Bring

  • 10+ years of experience building and scaling complex software or data platforms, including leadership of large initiatives
  • Demonstrated experience supporting AI/ML systems in production environments
  • Strong programming skills in one or more languages such as Python or Java
  • Experience with cloud-native architectures (e.g., AWS, Azure) and container orchestration (e.g., Kubernetes, Docker)
  • Deep understanding of data systems, including SQL and NoSQL databases, as well as modern data architectures
  • Familiarity with vector-based and graph-based data stores, caching layers, and high-throughput data processing systems
  • Experience building APIs and working with modern web architectures (REST, API gateways, SPAs)
  • Knowledge of machine learning frameworks such as TensorFlow, PyTorch, or similar tools
  • Hands-on experience working with large-scale data platforms and distributed processing technologies
  • Strong grasp of software engineering fundamentals, including data structures, algorithms, and design patterns
  • Experience with version control, CI/CD pipelines, and Agile development practices
  • Understanding of data governance, security, and privacy considerations (e.g., encryption, data protection strategies)
  • Strong problem-solving abilities and the ability to operate effectively in fast-paced environments
  • Excellent communication skills with the ability to collaborate across technical and non-technical teams

Nice to Have

  • Advanced degree in a technical field such as computer science, AI, or data science
  • Exposure to emerging areas such as generative AI, reinforcement learning, or autonomous systems
  • Experience with MLOps tools and frameworks
  • Background deploying ML models at scale in production environments
  • Familiarity with domain-specific applications of AI (e.g., regulated industries)
  • Prior hands-on experience as a data scientist or in applied machine learning roles
  • Understanding of distributed system design and microservices architecture